Shape features.
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:{caption:"Highly Cited",originalUrl:"/media/original/117"}},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\n'}],latestNews:[{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"451",leadTitle:null,fullTitle:"Implant Dentistry - The Most Promising Discipline of Dentistry",title:"Implant Dentistry",subtitle:"The Most Promising Discipline of Dentistry",reviewType:"peer-reviewed",abstract:"Since Dr. Branemark presented the osseointegration concept with dental implants, implant dentistry has changed and improved dramatically. The use of dental implants has skyrocketed in the past thirty years. As the benefits of therapy became apparent, implant treatment earned a widespread acceptance. The need for dental implants has resulted in a rapid expansion of the market worldwide. To date, general dentists and a variety of specialists offer implants as a solution to partial and complete edentulism. Implant dentistry continues to advance with the development of new surgical and prosthodontic techniques. \nThe purpose of Implant Dentistry - The Most Promising Discipline of Dentistry is to present a comtemporary resource for dentists who want to replace missing teeth with dental implants. It is a text that integrates common threads among basic science, clinical experience and future concepts. This book consists of twenty-one chapters divided into four sections.",isbn:null,printIsbn:"978-953-307-481-8",pdfIsbn:"978-953-51-6508-8",doi:"10.5772/964",price:139,priceEur:155,priceUsd:179,slug:"implant-dentistry-the-most-promising-discipline-of-dentistry",numberOfPages:490,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"af264376cc47bfd447ff2a0c2cf1bdc7",bookSignature:"Ilser Turkyilmaz",publishedDate:"October 3rd 2011",coverURL:"https://cdn.intechopen.com/books/images_new/451.jpg",numberOfDownloads:148230,numberOfWosCitations:42,numberOfCrossrefCitations:31,numberOfCrossrefCitationsByBook:3,numberOfDimensionsCitations:65,numberOfDimensionsCitationsByBook:6,hasAltmetrics:0,numberOfTotalCitations:138,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"October 12th 2010",dateEndSecondStepPublish:"November 9th 2010",dateEndThirdStepPublish:"March 16th 2011",dateEndFourthStepPublish:"April 15th 2011",dateEndFifthStepPublish:"June 14th 2011",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"26024",title:"Prof.",name:"Ilser",middleName:null,surname:"Turkyilmaz",slug:"ilser-turkyilmaz",fullName:"Ilser Turkyilmaz",profilePictureURL:"https://mts.intechopen.com/storage/users/26024/images/1852_n.jpg",biography:"Dr. Ilser Turkyilmaz obtained his dental degree from Hacettepe University, Ankara, Turkey in 1998. Immediately after graduation, he started his PhD program in the Department of Prosthodontics, Hacettepe University. He completed that program in 2004 and kept working as an instructor in the same department. Dr. Turkyilmaz then was invited by Goteborg University, Goteborg, Sweden for research collaborations. He worked in the Department of Biomaterials, Institute of Clinical Sciences, Sahlgrenska Academy, Goteborg University, Goteborg, Sweden in 2005. He returned to Hacettepe University in the end of 2005 and then worked in private practice in Ankara from February 2006 to May 2007. He was accepted for an implant prosthodontic fellowship program in the Department of Restorative and Prosthetic Dentistry, The Ohio State University, Columbus, Ohio, and worked in that university as an implant prosthodontic fellow from June 2007 to October 2008. He took up a full-time position as an assistant professor in the Department of Prosthodontics at the University of Texas Health Science Center in San Antonio, Texas, USA on November 1, 2008. Dr. Turkyilmaz maintains a private practice in the school’s faculty practice. He treats patients with esthetic and reconstructive needs using implants, veneers, crowns, fixed partial dentures, complete dentures, and partial dentures. Dr. Turkyilmaz is particularly interested in dental implant studies regarding early/immediate loading protocols, implant stability measurements using resonance frequency analysis, bone density evaluations using computerized tomography (CT), flapless implant surgeries using CT-generated surgical guides, and the biomechanical aspects of implants. He has currently 50 scientific articles published in well-known international journals. He has also given lectures including dental implants at local, national and international meetings. He is currently serving as an editorial board member or reviewer for several international dental journals. Dr. Turkyilmaz earned Diplomate status within the International Congress of Oral Implantologists in 2011, which is the highest honor showing efforts in education, research and actual clinical experience with dental implants.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"2",institution:null}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"998",title:"Oral Implantology",slug:"oral-implantology"}],chapters:[{id:"21543",title:"Various Ways to Enhance the Results of Maxillary Sinus Augmentation Procedures",doi:"10.5772/17264",slug:"various-ways-to-enhance-the-results-of-maxillary-sinus-augmentation-procedures",totalDownloads:5683,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:null,signatures:"Jun-Beom Park",downloadPdfUrl:"/chapter/pdf-download/21543",previewPdfUrl:"/chapter/pdf-preview/21543",authors:[{id:"27806",title:"Dr.",name:"Jun-Beom",surname:"Park",slug:"jun-beom-park",fullName:"Jun-Beom Park"}],corrections:null},{id:"21544",title:"Biomaterials Applicable for Alveolar Sockets Preservation: In Vivo and In Vitro Studies",doi:"10.5772/18459",slug:"biomaterials-applicable-for-alveolar-sockets-preservation-in-vivo-and-in-vitro-studies",totalDownloads:6545,totalCrossrefCites:3,totalDimensionsCites:9,hasAltmetrics:0,abstract:null,signatures:"Christiane Kunert-Keil, Tomasz Gredes and Tomasz Gedrange",downloadPdfUrl:"/chapter/pdf-download/21544",previewPdfUrl:"/chapter/pdf-preview/21544",authors:[{id:"31560",title:"Prof.",name:"Tomasz",surname:"Gedrange",slug:"tomasz-gedrange",fullName:"Tomasz Gedrange"},{id:"39526",title:"Dr.",name:"Christiane",surname:"Kunert-Keil",slug:"christiane-kunert-keil",fullName:"Christiane Kunert-Keil"},{id:"39527",title:"Dr.",name:"Tomasz",surname:"Gredes",slug:"tomasz-gredes",fullName:"Tomasz Gredes"}],corrections:null},{id:"21545",title:"New Bone Formation in the Maxillary Sinus With/Without Bone Graft",doi:"10.5772/16512",slug:"new-bone-formation-in-the-maxillary-sinus-with-without-bone-graft",totalDownloads:9767,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:null,signatures:"Dong-Seok Sohn",downloadPdfUrl:"/chapter/pdf-download/21545",previewPdfUrl:"/chapter/pdf-preview/21545",authors:[{id:"25392",title:"Prof.",name:"Dong-Seok",surname:"Sohn",slug:"dong-seok-sohn",fullName:"Dong-Seok Sohn"}],corrections:null},{id:"21546",title:"Bone Substitutes",doi:"10.5772/17329",slug:"bone-substitutes",totalDownloads:4500,totalCrossrefCites:4,totalDimensionsCites:9,hasAltmetrics:0,abstract:null,signatures:"Jesus Torres, Faleh Tamimi, Mohammad Alkhraisat, Juan Carlos Prados-Frutos and Enrique Lopez-Cabarcos",downloadPdfUrl:"/chapter/pdf-download/21546",previewPdfUrl:"/chapter/pdf-preview/21546",authors:[{id:"28009",title:"Dr.",name:"Jesus",surname:"Torres",slug:"jesus-torres",fullName:"Jesus Torres"},{id:"32861",title:"Dr.",name:"Faleh",surname:"Tamimi",slug:"faleh-tamimi",fullName:"Faleh Tamimi"},{id:"32862",title:"Dr.",name:"Mohammad",surname:"Alkhraisat",slug:"mohammad-alkhraisat",fullName:"Mohammad Alkhraisat"},{id:"32863",title:"Dr.",name:"Juan Carlos",surname:"Prados-Frutos",slug:"juan-carlos-prados-frutos",fullName:"Juan Carlos Prados-Frutos"},{id:"32864",title:"Dr.",name:"Enrique",surname:"Lopez - Cabarcos",slug:"enrique-lopez-cabarcos",fullName:"Enrique Lopez - Cabarcos"}],corrections:null},{id:"21547",title:"Dental Reconstruction Using Secondary Bone Graft Followed by Implant Placement in Alveolar Cleft of Patients with Cleft Lip and/or Palate",doi:"10.5772/17249",slug:"dental-reconstruction-using-secondary-bone-graft-followed-by-implant-placement-in-alveolar-cleft-of-",totalDownloads:5542,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:null,signatures:"Tetsu Takahashi",downloadPdfUrl:"/chapter/pdf-download/21547",previewPdfUrl:"/chapter/pdf-preview/21547",authors:[{id:"27757",title:"Prof.",name:"Tetsu",surname:"Takahashi",slug:"tetsu-takahashi",fullName:"Tetsu Takahashi"}],corrections:null},{id:"21548",title:"Bone Substitutes and Validation",doi:"10.5772/16956",slug:"bone-substitutes-and-validation",totalDownloads:6655,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,abstract:null,signatures:"Christopher Ogunsalu",downloadPdfUrl:"/chapter/pdf-download/21548",previewPdfUrl:"/chapter/pdf-preview/21548",authors:[{id:"26785",title:"Dr.",name:"Christopher Olubode",surname:"Ogunsalu",slug:"christopher-olubode-ogunsalu",fullName:"Christopher Olubode Ogunsalu"}],corrections:null},{id:"21549",title:"Immediate Dental Implants and Bone Graft",doi:"10.5772/16522",slug:"immediate-dental-implants-and-bone-graft",totalDownloads:9512,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:null,signatures:"Khalid S. 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",isbn:"978-1-80356-588-0",printIsbn:"978-1-80356-587-3",pdfIsbn:"978-1-80356-589-7",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,isNomenclature:!1,hash:"3731c009f474c6ed4293f348ca7b27ac",bookSignature:"Dr. Asghar Ali Kamboh",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11578.jpg",keywords:"Beneficial Microorganisms, Probiotic Role in Health and Immunity, Supplementation of Probiotics in Poultry, Dietary Supplementation of Yeast in Farm Animals, Gut Health, Probiotic and Mucosal Immunity, Probiotics and Intestinal Architecture, Probiotics and Nutrient Absorption, Ban of Antibiotics in Food Animals, Regulatory Issues of Antibiotic Use in Farm Animals, Alternatives to Antibiotic in Animal Production, Consequences of Antimicrobials Use in Animals",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"March 15th 2022",dateEndSecondStepPublish:"June 3rd 2022",dateEndThirdStepPublish:"August 2nd 2022",dateEndFourthStepPublish:"October 21st 2022",dateEndFifthStepPublish:"December 20th 2022",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"a month",secondStepPassed:!0,areRegistrationsClosed:!1,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:"A well-known researcher in the area of Veterinary Sciences with a key interest in Veterinary Microbiology and immunology. 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According to the International Agency for Research on Cancer (IARC) [1], part of the World Health Organization (WHO), there were 8.2 million deaths caused by cancer in 2012 and 27 million of new cases of this disease are expected to occur until 2030 [2].
Cancer, medically defined as a malignant neoplasm, is a board group of disease involving unregulated cell growth [2]. In cancer, cell divides and grows uncontrollably forming malignant tumors, invading nearby parts of the body. The cancer can spread to all parts of the body through the lymphatic systems or blood streams [3].
Cancer can be diagnosed by classifying tumors in two different types such as malignant and benign. Benign tumors represent an unnatural outgrowth but rarely lead to a patient’s death; yet, some types of benign tumors, too, can increase the possibility of developing cancer [4]. On the other hand, malignant tumors are more serious and their timely diagnosis contributes to a successful treatment. As a result, predication and diagnosis of cancer can boost the chances of treatment, decreasing the usually high costs of medical procedures for such patients [5].
Breast cancer (BC) is the most commonly diagnosed cancer and the most common cause of death in women all over the world. Among the cancer types, BC is the second most common cancer for women, excluding skin cancer [6]. Besides, the mortality of BC is very high when compared to other types of cancer [7]. BC, similar to other cancers, starts with a rapid and uncontrolled outgrowth and multiplication of a part of the breast tissue, which depending on its potential harm, is divided into benign and malignant types.
Generally, there are two types of BC that are in situ and invasive. In situ starts in the milk duct and does not spread to other organs even if it grows [8]. Invasive breast cancer on the contrary, is very aggressive and spreads to other nearby organs, and destroys them as well [9]. It is very important to detect the cancerous cell before it spreads to other organs; thus, the survival rate for patient will increase to more than 97% [10].
A major class of problems in medical science involves the diagnosis of disease, based upon various tests performed upon the patient. The evaluation of data taken from patients and decisions of experts are the most important factors in diagnosis. The correct diagnosis of BC is one of the major problems in the medical field. As BC can be very aggressive, only early detection can prevent mortality. Clinical diagnosis of BC helps in predicting the malignant cases and timely diagnosis can increase the chances of a patient’s life expectancy from 56 to 86% [11].
BC has four early signs: microcalcification, mass, architectural distortion, and breast asymmetries [12]. The various common methods used for breast cancer diagnosis (BCD) are positron emission tomography (PET), magnetic resonance imaging (MRI), CT scan, X-ray, ultrasound, photo-acoustic imaging, tomography, diffuse optical tomography, elastography, electrical impedance tomography, opto-acoustic imaging, ophthalmology, mammogram, etc. [13]. The results obtained from these methods are used to recognize the patterns, which are aiming to help the doctors for classifying the malignant and benign cases.
Despite of recent advances in the comprehension of the molecular biology of BC progression and the discovery of new related molecular markers, the histopathological analysis remains the most widely used method for BC diagnosis [14]. Despite significant progress reached by diagnostic imaging technologies, the final BCD, including grading and staging, continues being done by pathologists applying visual inspection of histological samples under the microscope [15].
However, manual classification of images is a challenging and time-consuming task, being highly susceptible to interobserver variability and human errors, resulting in extremely poor critical outcomes, thus markedly increasing the workload of radiologists because of their significant shortage. In addition, medical care costs that are relevant to imaging rapidly increase. Therefore, new methods for diagnosis are required.
Currently, bioimaging quantification is an emerging technique in the field of radiology with a growing implantation in hospital centers. It provides relevant information that is not appreciable by the naked eye in conventional radiological reading. It consists of the generation of quantitative (numerical) data from images, mainly of high resolution, to provide information on which to support a clinical assessment [16]. Biomarkers can be said to be the transition from radiology to personalized medicine.
Bioimagen markers allow to characterize and to study different diseases using some kind of information, such as genetic, histological, clinical imaging, etc. These biomarkers can be used to detect abnormalities in the data as genetic mutations that cause some diseases and can also be used in the clinic for the detection of patients with some types of disease [17].
The application of quantification of bioimaging markers to aid in the diagnosis, treatment, and follow-up of pathologies provides added value throughout the clinical practice process by providing additional information to conventional diagnostic tests [18]. From imaging tests processed in the right way, abnormalities in a tissue are evidenced before they are perceptible in the reading of the radiologist, fundamental objective of this type of biomarkers [19]. In addition, they allow the monitoring of the treatment effect from a quantitative point of view.
As mentioned before, BC is one of the leading causes of death in women around the world, accounting for nearly one-third of cancer-related deaths. Currently, the clinical screening by mammography is the most effective way for the early detection of this disease. Using analysis of mammograms obtained through X-rays allows radiologists to visualize early signs of cancer, such as calcifications, masses, and architectural distortions among other early signs of cancer. However, this analysis is a routine, monotonous, and exhausting task and it is estimated that only 0.3–0.4% of the cases are actually carcinogenic [20].
It has been shown that because of these problems and other factors intrinsic to cancer such as obscuration of abnormalities by fatty tissue, a radiologist can omit up to 30% of cancers. Moreover, because this type of analysis produces many false positives, the number of unnecessary biopsies is increased up to 35%, causing a high level of stress in the patient, and in turn saturating the health systems [21].
Due to all the problems presented by mammography screening, great efforts have been made to support the radiologist in the search for these lesions through computer-aided detection (CAD) or biomarker systems, which try to help the radiologist by taking advantage of the latest advances in computer vision and their manipulation in digital form [22].
At present, computer-aided detection/diagnosis (CAD/CADx) systems are one of the numerous major research topics in diagnostic radiology and medical imaging. CAD systems allow the radiologist to manipulate mammography to highlight certain features that would otherwise be difficult to visualize. One of the most used techniques is the improvement of contrast, which allows to highlight objects in areas of low intensity. To date, CAD is a more suitable method for primary diagnosis of cancer in computed tomography, X-ray, MRI, or mammogram images. CAD system is an effective intermediate between input images and the radiologist. The output from CAD is not considered as an end result; nevertheless, the result is used as reference with regard to additional testing in the related field [23].
The CAD approach helps medical doctors to diagnose diseases with a higher degree of efficiency, while minimizing examination time and cost, as well as avoiding unnecessary biopsy procedures. However, CAD systems not only allow a better visualization of mammograms, but also using different digital image processing (DIP), knowledge discovery from data (KDD), artificial intelligence (AI) techniques such artificial neural networks (ANN) allow to preselect certain regions of interests (ROIs) for later analysis by the radiologist [24].
Classification of histopathology images into distinct histopathology patterns, corresponding to the noncancerous or cancerous condition of the analyzed tissue, is often the primordial goal in image analysis systems for cancer automatic-aided diagnosis applications. Recent advances in DIP, KDD, and AI techniques allow to build CAD/CADx that can assist pathologists to be more productive, objective, and consistent in diagnosis. The main challenge of such systems is dealing with the inherent complexity of histopathological images.
The aim of this research is to use advanced DIP to investigate and develop specific imaging biomarkers for Mexican patients through the quantitative mammography analysis and with this information to develop technology based on advanced KDD and AI techniques, aiming to detect breast cancer in the early stages in order to support the diagnosis and prioritization of high-risk patients.
In this research, the study of BC disease using advanced techniques of DIP, KDD, and AI was carried out in order to develop imaging biomarkers that allow to carry out diverse studies for BCD. As is showed in Figure 1, the research was divided in three main stages.
Main stages of research.
Currently, there are no public databases of BC in Latin America or Mexico. Therefore, at first stage, different public mammography databases were used for developing and validating digital image processing algorithms capable to select ROIs from mammograms to extract image features used to train a generalized regression artificial neural network (GRANN). The aim was to generate a methodology for the characterization of mammograms and their association with risk factors in BC patients as well as to integrate and to develop the technological tools for mammography analysis for BCD using AI technology. In this work, results obtained at first stage are presented.
Because there are no public databases of BC for Mexican patients, it was proposed to establish two protocols for the acquisition of mammograms. The first protocol, second stage, seeks to obtain data retrospectively, which will allow obtaining the mammograms necessary to validate in Mexican patients the methodology and technological tools developed at stage one. The aim of the second stage is the generation of an anonymous database of Mexican patients for free use by the scientific community for the study of BC in Mexican patients and to validate the methodologies developed in collaboration with the General Hospital of Zacatecas (GHZ) and the Molecular Medicine Laboratory (MML) from Autonomous University of Zacatecas, Mexico.
In the second protocol, third stage, it is sought to generate a long-term prospective protocol, which will allow the creation of a database with different risk factors associated with the development of BC. This protocol will allow to collect clinical data of patients with both high and low probabilities of developing cancer. These data will be able to validate the methodologies of cancer detection by the scientific community.
The generation of a prospective protocol will allow the expansion of the database for the study of breast cancer in Mexican patients. Unlike the retrospective protocol, prospective protocol aims to include clinical data, risk factors, and mammograms, among others. This database would present to the scientific community a reference for the development of new breast cancer detection techniques in Mexican patients.
Patient prioritization can play a very important role in the reach of health services in developing countries such as Mexico, where not all have access to these specialized oncology services. Therefore, this research seeks the study of BC by generating a methodology that allows the detection of patients with a high probability of BC. In this work, a new technology to generate mammographic biomarkers and a CADx system for breast cancer diagnosis was designed in order to analyze Digital Image Mammograms (DIM). With this knowledge, it is proposed to create a biomarker specifically designed for the Mexican population. As is showed in Figure 2, the first stage was divided into six main stages.
First stage of research. Mammographic feature extraction and artificial neural network training.
The development of CAD/CADx systems involves their generation and validation by using mammograms obtained from clinical studies, or using public databases. However, at the global level, there are few public databases available to the scientific community to investigate. As mentioned before, currently, there are no public databases of BC in Latin America or Mexico for conducting this kind of studies. Therefore, at first stage, different public mammography databases were used for developing and validating digital image processing algorithms capable to select ROIs from mammograms and to extract image features used to train a GRANN capable to diagnose BC as an aid for radiologists.
Currently, there are only three public databases to conduct this type of research: the first one is the Digital Database for Screening Mammography (DDSM) that has a total of 2620 cases distributed in 625 normal, 1011 benign and 914 malignant and includes the two standardized views CC and MLO. Another available database is the Mammographic Image Analysis Society - Digital Mammogram Data Base (mini-MIAS) that has 322 cases; however, it only has the MLO view. DDSM and mini-MIAS databases are both form North America.
A newly created database is the Breast Cancer Digital Repository (BCDR) from Europe. The creation of BDR is supported by the IMED Project (Development of Algorithms for Medical Image Analysis). The IMED project was created by INEGI, FMUP-CHSJ University of Porto, Portugal and CIEMAT, Spain from 2009 to 2013. This database has 724 patients (723 women and 1 man), aged between 27 and 92 years.
In the first stage of this research, the mini-MIAS, DDSM, and BCDR databases were used to generate and validate the development of a biomarker, an artificial neural network approach with incremental learning and with both, the design of a CADx methodology, carried out in a general scope. However, it is important to highlight that these databases are formed by patients with ethnic characteristics typical of their region, which makes it difficult to transfer knowledge to other countries and their own features.
Moreover, as has been shown by the scientific community, BC varies widely between different etiologies and may prove that systems created for a population may not work for a different population in the way they were thought. This is further aggravated by different types of diets, customs, and lifestyle. Due to this, the development of biomarkers and CAD systems for the Mexican population needs an adaptation to the characteristics of our population. In second and third stages of this research, the designed methodology will be focused and refined for its operation in Mexican patients.
In this work, results obtained with BCDR database are presented. BCDR database contains useful information of each mammogram such as gender: masculine or feminine; segmentations of mammogram, marked in red pixels the ROI that contains the lesion found by the radiologist; patient ID; the age of the patient; breast density, i.e., the percentage of breast density according to Breast Imaging Reporting and Data System (BI-RADS) standard expressed as percentage of glandular and fibrous tissue; breast localization, depending on the location of breast of the RIO with the lesions; mammography, the type of lesion found by the mammographic image expert; biopsy result, anatomical pathology of the biopsy; categorization of the definitive diagnosis; the BI-RADS classification of the lesion; and finally, intensity and shape descriptors of ROI. However, it is important to mention that for this research, these descriptors were not used to train the neural network. Instead, a set of computer algorithms were designed in order to extract image descriptors of ROI of mammograms as described in later section.
A mammogram image can be considered as a representation of the X-ray radiation density that reflects the tissue of the breast. A risk factor for BC in a patient is recognized when a white region appears on the mammogram image, which means a high tissue density, that may be considered abnormal. A breast abnormality is commonly called ROI. According to DIP techniques, segmentation of breast abnormalities on mammograms is a crucial step in CAD systems. It is a difficult task, since these types of medical images are in low-intensity contrast, making it difficult to identify the edges of a suspicious mass.
In the methodology used in this research, only lateral mammographic images taken from BCDR database were used. In all selected images, a lesion exists, which is considered as benign or malignant; digital mammographic images of BCDR database can be accessed in two forms: the first one from films (photographic films) and the second one from digital images taken from X-ray system (mammography images). Films’ images require the design of digital image processing algorithms to eliminate artifacts such as red pixels and prenoise such as labels used by radiologists to identify left or right breast as well as patient identification information. Conversely, digital mammography images only require the design of algorithms for removing red pixels.
The films approach improves digital mammography images increasing the high frequency and eliminating the noise and unwanted artifacts in the ROI. As can be appreciated in Figure 3, at preprocessing stage, a computer tool was designed to automate the preprocessing of film digital mammographic images (FDMIs). All FDMIs are treated to eliminate image artifacts such as background, noise, and image labels. In the FDMIs, a common threshold was applied to create a region of the breast and other regions with the labels and artifacts on the mammography.
Preprocessing of a mammographic image. (a) Original image, (b) breast region, highlighting labels and background noise, (c) clean breast binary image, and (d) mammography image cleaned.
Using the designed automated computer tool, after creating the logical image, all small regions (less than 10,000 pixels) are eliminated to remove the regions considered as unnecessary in FDMIs. Then, the logical image (mask) is used instead of the original image to obtain an image of the breast without artifacts and labels. Figure 3 shows the preprocessing method to remove noise and labels in a digital mammography image.
Converting a greyscale to a digital or logical image is a common task of digital image processing. There are many methods for calculating the threshold value for creating logical images. As can be appreciated in Figure 4, in this research, the threshold was calculated by converting the nonzero pixel’s values to 1. To create a logical image that contains the ROI and the pectoral muscle, the gray tones were converted to white level.
Pectoral region removing process.
For removing the pectoral region in the logical image, as is showed in Figure 4, the white region that is connected to the border of the binary image was eliminated. Therefore, the surplus white region represents the ROI detected in the mammography image. With a cleaned image, the next step is the segmentation process.
On the other hand, the digital mammographic approach works as follows: to calculate the descriptors, the ROI of the lesion is manually segmented by the expert radiologist as can be appreciated in Figure 5. At preprocessing stage, the image is fitted for the segmentation. The pixels in red are turned into black. Using the black pixels, the ROI is separated from the rest of the breast image for making a segmentation of the ROI as is showed in Figure 6.
Preprocessing stage of digital mammogram approach.
Binary mask and ROI in tones of grays.
For the segmentation of the ROI, a binary or logical image with a very high binarization threshold is created where low gray levels become white. This approach considers most of gray pixels of the image looking not to lose many pixels from ROI. Afterward, the white logical region that is connected to the edge of the mammographic image is removed. Some white pixels pertaining to the contour of the breast are discarded when the pixels in the image with a small area are removed. Finally, the white region with a greater number of pixels is extracted, which would be considered as the neoplasia.
Next, a binary mask is created using the ROI obtained in the segmentation stage. With the mask and together with the complete image in shades of gray, we will get the ROI in shades of gray as is showed in Figure 6.
The next step in the operation of regular CAD systems is the feature extraction of the RIO. The feature extraction can be defined as the process to infer and quantify the parameters that characterize the object being studied. The feature extraction contributes to the analysis of the ROI. It is possible to quantify the shape, texture, size, border, and other tissue parameters that can contribute to the diagnosis and detection of a cancer risk factor. As is showed in Figure 7, in this work, shape, intensity, and texture features were extracted in order to create a biomarker for BCD using a CADx system that uses AI technology.
Image features extracted.
The image features of all Digital Image Mammography (DIM) of BCDR database were extracted and used to build a biomarker to train an ANN. The BCDR digital images are in RGB and gray-level digitalized in JEPG format with a depth of 24 and 8 bits per pixel, respectively, and a resolution of 3328 × 4084. The RGB mammograms are used to show the red remarked section by a radiologist to delimit the found anomaly.
The segmentation process use the red section remarked in the RGB mediolateral oblique view mammograms to obtain the ROI. In the RGB mammograms, all the red pixels in the image and the pixels outside the original red region were eliminated. Finally, the remained pixels in the gray-level mammogram were used to get the ROI used for the features’ calculation.
Using a custom-designed automated computer tool, a total of 361 images (36 malignant and 325 with benign abnormalities) from 239 patients were segmented in order to get the RIOs. This information was used as the entrance data for training and testing a GRANN. This computer tool saves a lot of time in the preprocessing stage of mammography analysis. This tool will be used at second and third stages of research to analyze the mammograms of Mexican patients in order to create a Mexican biomarker and a CADx system for BCD.
Feature extraction of digital images, such as obtained in digital mammograms, as is showed in Figure 7, is a manner to represent an element or an ROI in an image like a fingerprint, and these features are used in many research areas such as machine learning, patter recognition, image processing, or diagnosis of disease in medical science. Feature extraction is a crucial task before classifying an ROI or a pattern in an image.
Image processing is the most important area where the feature extraction is applied, in which mathematical algorithms are used to detect and isolate various desired portions or shapes, features, of digitalized images or video streams, it is particularly important in the area of pattern recognition or character recognition.
The feature extraction method is the measure of physical parameters visualized in a segmented region of an image. The aim of feature extraction is to find a mathematical way to represent the image information, which is important, in a compact form, for solving a computational task. In BCD, these features help to determine the kind of tumor detected in a mammogram image. The choice of features has a crucial influence on the accuracy of classification, the time needed for classification, the number of examples needed for learning, and the cost of performing classification. In breast abnormalities, classification of the differences in mass between benign and malignant on a mammography can be distinguished from their shape, textures, and the intensity in the image.
In this research, an automated computer tool was designed to calculate shape, intensity, and texture features from ROI extracted from BCDR mammograms. The shape features of MDI use the pixels inside and the border of the ROI. These descriptors, showed in Table 1, only have a valid meaning in binary or logical images, and some simple shape features are used to describe a ratio between some geometrical figures; for example: extend, ellipse_ratio, and solidity. Most common shape features are the area and perimeter of the region, but they are applied when the ROI size is invariant. However, the area and perimeter can be used to create a relation as the circularity and compactness.
Shape features | |
---|---|
Circularity | Extend |
Compactness | Ellipse_ratio |
Solidity | |
Shape features.
The intensity features, showed in Table 2, use the shape intensity histogram to get information that describes the image; i.e., the intensity features use the probability and statistics from the values of the pixels in the image. The mean is the average intensity level. The standard is used to quantify the amount of variation of the set of intensities levels. The variance refers to the variation of the intensities around the mean value. The coefficient of variation is a standardized measure of dispersion in the values. Finally, the skewness and kurtosis measure the histogram symmetric.
Intensity features | Texture features |
---|---|
Mean | Energy |
where | |
Standard deviation | Contrast |
Variance | Correlation |
where | |
Coefficient of variation | Homogeneity |
Skewness | Entropy |
Kurtosis | |
Intensity and texture features.
The texture features, Table 2, describe the
As before mentioned, medical diagnosis is an important and complicated task that needs to be executed accurately and efficiently. At present, new techniques based on data mining, KDD, and AI in healthcare are being used mainly for predicting various diseases as well as assisting doctors in diagnosis in their clinical decision. One area where this effort has been most felt is the diagnosis of breast cancer in women. However, the absence of any fully effective, efficient method of BCD has led researchers to develop automated computational systems. In this research, automated CADx technology based on ANN as decision-making tool in the field of BCD is being developed.
For automatic classification of BC on DIM, a GRANN was used to separate malignant and benign tumors [25]. GRANN falls into the category of probabilistic neural networks (PNN) [26, 27, 28, 29, 30]. GRANN is a neural network architecture of one-step-only learning that can solve any function approximation problem. The learning process is equivalent to finding a surface in a multidimensional space that provides a best fit to the training data. During the training process, it just stores training data and later uses it for predictions. This neural net is very useful to perform predictions and comparisons of system performance in practice. In GRANN architecture, there are no training parameters, just a smoothing factor (σ) that is applied after the network is trained. The choice of this factor is very important [26, 27, 28, 29, 30].
In this research, as is showed in Figure 8, a GRANN was trained and tested using a data set of 361 mammograms extracted from BCDR public database. For each mammogram, 35 image descriptors were calculated through an automated computer tool specifically designed for this purpose. These image features were used to train the neural net in order to classify benign and malignant BC for decision making in BDC.
Training of GRANN for BCD. (a) Breast image, (b) segmentation, (c) image descriptors, (d) network training, and (e) BCD.
As can be appreciated from Figure 8, the image features were used as entrance data, and the malignant (cancerous) and benign (noncancerous) instances were used as output data. In order to train the network, the dataset was randomly divided into two subsets, one with about 80% of the instances to training and another with around the remaining 20% of instances to testing.
After 2000 network trainings, a smoothing factor equal to 1e−4 was calculated. This value was used for training the neural net reaching an accuracy of 95.83%. The results obtained in this work show that GRANN is a promising and robust system for BCD. The performance of a trained GRANN was evaluated using four performance measures: accuracy, sensitivity, specificity, and precision. These measures are defined by four decisions: true positive (TP), true negative (TN), false positive (FN), and false negative (FN). TP decision occurs when malignant instances are predicted rightly. TN decision benign instances are predicted rightly. FP decision occurs when benign instances are predicted as malignant. FN decision occurs when malignant instances are predicted as benign.
Accuracy can be calculated as:
Sensitivity can be calculated as:
Specificity can be calculated as:
Precision can be calculated as:
The confusion matrix for the data set, showed in Table 3, was computed using these values into above equations to find accuracy, sensitivity, specificity, and precision. Table 3 shows the classification results of BC. The confusion matrix is a table that allows to visualize the execution of an algorithm, usually a supervised learning. In this case, it is a classifier of two classes, the current or expected and those obtained by the system (predictions). Each column of the matrix represents the cases that the system, in this case, the neural network, predicted, while the rows represent the expected values.
Obtained | ||||
---|---|---|---|---|
0 | 1 | |||
Goal | 0 | 66 | 2 | |
2.80% | ||||
1 | 1 | 3 | ||
1.40% | ||||
95.80% | ||||
4.20% |
Confusion matrix.
The diagonal indicates the successes achieved by the system; that is, the trained neural network obtained 91.7% + 4.2% = 95.8% of accuracy, successfully predicting 66 + 3 = 69 lesions of a population of 72, representing an error of 4.2% with three errors from a population of 72 lesions.
With both biomarkers obtained from mammograms and the trained GRANN, a CADx technology system, as showed in Figure 9, is being created to be used at second stage in collaboration with GHZ and MML.
CADx system being developed based on DIP, KDD, and AI methodologies.
The Computer Aided Diagnosis system consists of two main stages: the first one detects the suspicious regions with high sensitivity presenting the results to the radiologist aiming to reduce false positives. This process is given in the first instance by a preprocessing algorithm based on advanced DIP techniques designed to reduce the noise acquired in the image and in an improvement of the same, and then it executed a segmentation process of different ROIs designed to detect high suspicion of some signs of cancer. By using the information obtained in the segmentation process, the classification of positives or negatives prediction of BC is obtained through a GRANN. After concluding the development of this CADx technological computer tool, it is planned to be used at real workplaces such as GHZ, making a validation of the prediction obtained by the neural network compared with predictions made by specialized oncologists aiming that it can be used as an aid in the early breast cancer diagnosis.
The aim of developing this CADx system for Mexican patients is to expand the knowledge of the database of BCD including image mammograms information, clinical data, risk factors, biopsy results, genomic information, etc., as is showed in Figure 9, at the bottom of the main window, with the aim to obtain more information on the resulting diagnostics such as degree of malignancy, time of presence, etc.
As mentioned before, conventionally, BCD and classification is performed by a clinician or a pathologist by observing stained biopsy images under the microscope. However, this is time consuming and can lead to erroneous results. Therefore, there is a rise in the need for developing intelligent and automated technology. As this problem can be computationally modeled as a problem of retrieving relevant information from a plethora of reports or tests, the development of a computationally efficient and detection-wise effective system for BCD can be seen as an issue from the field of KDD. Being cross-dimensional, KDD uses algorithms and techniques from a vast array of fields like soft computing, pattern recognition, machine learning statistics, artificial intelligence (AI), natural language processing (NLP), etc.
In this research, a method based on advanced DIP, KDD, and AI techniques was used for the extraction of fundamental features in DIM in order to detect breast lesions by using a GRANN. The used methodology was divided in two main stages. The first one used advanced DIP techniques for extracting image features of DMI in order to create a biomarker for BCD. With this information, in the second stage, a GRANN was trained and tested in order to classify BC.
After 2000 network trainings, a smoothing factor equal to 1e−4 was calculated. This value was used for training the neural net reaching an accuracy of 95.83%. The performance of trained GRANN was evaluated using four performance measures: accuracy, sensitivity, specificity, and precision. The results obtained in this work show that GRANN is a promising and robust system for BCD.
In a third stage, a CADx system based on AI technology is being designed in order to be applied in Mexican patients in collaboration with GHZ and MML. The proposed system aims to eliminate the unnecessary waiting time as well as reducing human and technical errors in diagnosing BC. The Laboratorio de Innovacion y Desarrollo Tecnologico en Inteligencia Artificial is seeking collaboration with research groups interested in validating the technology being developed.
This work was partially supported by Fondo Sectorial de Investigación para la Eduación under contract no. 241771 and PRODEP under contract no. 511-6/17-7763. The second and sixth authors want to thank the postdoctorate and doctorate scholarships, with scholarship holder numbers 25467 and 25976, respectively, received by Fondo Sectorial de Investigación para la Eduación under contract no. 241771. The fourth and fifth authors want to thank CONACYT PNPC scholarships, with scholarship holder numbers 285593 and 577554, respectively, received through Posgrado en Ingenieria y Tecnologia Aplicada, member of Programa Nacional de Posgrados de Calidad (PNPC) of CONACYT, México.
Authors want to thank the participation of Arturo Serrano Muñoz, an undergraduate student of Information Technology and Communication Bachelor from Universidad Tecnologica del Estado de Zacatecas, México, who is receiving a scholarship from PRODEP under contract no. 511-6/17-7763. This student performed the installation and configuration of the software and several services on the server where calculations were performed for extracting the features of the mammographic images and the neural network trainings.
Authors want to thank the participation of Edgar Viveros Llamas, an undergraduate student of Robotics and Mechatronics Bachelor from Universidad Autonoma de Zacatecas, Mexico. This student is making a social service in Laboratorio de Innovacion y Desarrollo Tecnologico en Inteligencia Artificial, helping with general activities related to this research.
Any human being needs the water as the second most important fluid after air to be able to live on the Earth. Actually, around two-thirds of the Earth is covered by water (~ 71%), but more than 7% of this water cannot be used because they are in the form of ocean, ice caps, glaciers, ground, and aquifers [1]. Therefore, the freshwater that is available to use by the people is only around 1% all over the globe. So, the need for desalinated freshwater arises day by day [2]. In addition, the applications of freshwater such as cooking, drinking, and farming make it in a difficult situation. As a result, providing safe drinking water is a major challenge all over the world [3, 4]. The predicted freshwater shortage problem in 2030 is illustrated in Figure 1.
Estimated global water scarcity in 2030 [
The simplest well-known cycle for the water is the hydrological cycle, which had sequentially the steps of water surface evaporation, condensation, cloud creation, runoff, and rain. So, the water controls the ecosystem of any society [6, 7]. This is because the potable water shortage is a problem of both the remote and urban communities [8].
The thermal desalination processes follow the same principles of the natural hydrological cycle, but they use huge energy amounts. Distillation is accomplished by introducing saltwater into the process, which produces two output streams: one of freshwater and the other of brine water. Distillation of seawater produces freshwater [9, 10, 11, 12, 13].
Distillation becomes a key source of freshwater for most of the world’s regions. Because of the ample water, the distillation procedure is mostly considered in coastal places. The most significant feature of this procedure is that it is completely safe for everyone involved—in other words, it has no negative consequences for the environment [14]. According to a survey conducted in the preceding decade, roughly 75 million people around the world rely on distillation for their everyday requirements. Distillation is the only source of freshwater for many countries. Saudi Arabia, the United States, the United Arab Emirates, Spain, and Kuwait are the top five countries in terms of desalination plant capacity, with 17.4, 16.2, 14.7, 6.4, and 5.8%, respectively [15]. The capacity of distillation processes for various countries is depicted in Figure 2; for (a) the globe, (b) USA, and (c) Middle East countries in 2002.
Capacity of distillation processes for (a) the globe, (b) USA, an (c) Middle East countries in 2002 [
Till 2015, the total capacity of desalinated freshwater is 86.55 million cubic meter a day, which were obtained from around 18,000 plants for desalination around the globe. The Middle East and North Africa account for almost 44% of the above total capacity. Over the last 20 years, 80% of the energy utilized for freshwater producing has been lowered because of contemporary advancements in distillation technologies [16].
Desalination of brackish/saline water can be done in a variety of ways. Among the distillation methods, multistage flash desalination (MSFD), multi-effect distillation (MED), and reverse osmosis (RO) are considered the most commercial and economic viable technologies for distillation. These techniques are the most effective, and they will continue in the future [17]. Desalination can be done in several ways, as listed below.
MSFD is based on flashing of evaporation. Evaporation of saltwater occurs as a result of a decrease in pressure rather than a rise in temperature. Broadly speaking, regenerative heating is used to achieve a maximal production and best MSFD’s economics. The seawater flashing in the flashing chamber regenerates and transfers its thermal energy to the saltwater passing
Multistage evaporators, with roughly 19–28 stages, are utilized in recent MSFD plants [20]. The MSFD operating temperatures are between 90 and 120°C. The more the operating temperature of unit, the higher the efficiency of the system. Also, the pressure should be controlled under the water saturation temperature.
In the unit (see Figure 3), various devices or accessories such as demisters, decarbonators, and vacuum deaerators are employed for various reasons. Demisters are used to prevent the carryover of saline water into condensed distillate. Removing the dissolved gases in brine is the function of decarbonator and vacuum deaerator [22].
Illustration of processes of MSFD [
MED method is the earliest of all distillation techniques. Thermodynamically, it is the most constitutional technique among all other distillation methods. The term “effect” of the MED name refers to how many evaporators’ series. Then, the main fundamental of MED is the decrease in ambient pressure through various effects. In this process, no additional heat is required after the first effect. This is due to that MED automatically makes the saline water to be boiled many times through the corresponding pressure.
In this process, the saline water temperature is increased to its boiling value at the first effect through the heat exchanger tubes. The entering saline water is sprayed over the evaporator surface for better vapor generation. The created vapor is condensed on the other side of tubes. On the second hand, the condensation process is utilized on the same time to heat up the saline feedwater. Figure 4 illustrates the desalination with solar energy.
Desalination by solar energy [
MED economy relies on its effects number regarding its chained processes [8]. So, the first effect has some generated vapor from the seawater entering the effect. After that, the remaining water is fed to the next effect. The amid tubes are warmed up using the first-effect created vapor. Also, that vapor is condensated to produce potable water. Besides, the generated vapor heats up the remaining saline water of the next effect. This action is repeated from one effect to another under low pressure and temperature till the end of process with around 4–21 effects [23].
As it is known, raising the pressure of steam vapor leads to increase its temperature, and hence, the heat released from this vapor is increased. This concept is utilized in the VCD method, where the vapor-increased heat is utilized to evaporate the incoming saline water. So, the main key of VCD is reducing the medium pressure, which leads to decrease the boiling temperature of water [24]. This process can be achieved by either steam jet technique (thermo-compressor technique) or mechanical compressor device (electrically driven technique), and these techniques are utilized to condense vapor content into distillate and use the corresponding latent heat as a heat source for evaporating the incoming saline water.
In the technique of thermo-compressor, a venturi orifice is used in the stream of steam jet to create low pressure. After that, the vapor content is compressed
In addition, there is another kind of VCD, which depends on lowering the temperature inside the VCD, and hence, this kind needs only power to run. This technique of VCD is useful for small desalination units due to its simple construction, better efficiency, and process reliability [25]. As a result, VCD is applicable in resorts, industries, and drilling sites.
It is known that the water flows naturally from the freshwater direction to saltwater direction. RO depends mainly on a critical parameter called osmotic pressure, which should force the saltwater to flow in the opposite direction of natural flow. As a result, we need an external source of pressure to overcome the osmotic pressure. That external pressure must be more than the osmotic pressure. Hence, the name of this method (reverse osmosis) refers to the process meaning reversing the direction of normal water flow through the membrane. By applying this process, the salts in the saline water are left behind and not allowed to cross the membranes [26]. This process produces potable water (permeate) and brine water (concentrate) as illustrated in Figure 5. Also, Figure 5 illustrates the main components of RO unit such as the pretreatment, membranes, high-pressure pumps, and post-treatment.
Schematic of RO desalination technique [
The pretreatment process is important for eliminating the undesirable materials that damage the membrane [27]. It relies on the membrane kind and configuration, properties of feedwater, recovery ratio, and required permeate quantity and quality. According to those parameters, the pretreatment process has different techniques to be applied such as chlorination, coagulation, acid addition, micron cartridge filtration, multimedia filtration, and dechlorination. Moreover, to overcome the osmotic pressure, high-pressure pumping system such as the centrifugal pump is utilized. Additionally, the different membrane configurations such as the spiral wound and hollow fine fiber (HFF) strongly affect the performance of the RO unit [28]. Besides, adjusting the pH and adding H2S and CO2 are performed in the post-treatment process [29].
Another type of desalination processes is nominated freezing, which is simple to conduct and operate. This process depends mainly on the fact that the dissolved salts are removed while forming the ice crystals from the saline water. First, we clean and wash the saline water mixture to leave the salt in the left water behind before freezing the whole water. Then, we can get the freshwater
Freezing units have the merits of low power consumed, few corrosions, and eliminated scaling factors. But it has the demerits of handling water and ice mixtures because it is mechanically hard to treat. Unfortunately, this method still needs numerous improvements to be applied on the commercial level. Limited freezing stations exist all over the globe such as that was built in Saudi Arabia [31].
Here, the sun energy is the driving force for such solar desalination systems, which actually are alike the natural hydrological cycle. The natural hydrological cycle takes every day in the form of heating the seawater using the solar radiation to produce vapor, and this vapor content is condensated due to the low temperature in the heights. An application on the solar distillation systems is the greenhouse solar distiller [25, 32].
This process is almost linked to MSFD systems. This is because MSFD produces distillate with small impurities amounts, and then, the potabilization is utilized to eliminate these impurities [33]. The potabilization process can be conducted
The economics of any system determine its success. In desalination stations, the parameters of fixed cost, running costs, station location, maintenance cost, and energy consumption are the controlling factors of the station economics. There are two opposite directions for determining the economics of the desalination systems. First is the improvements in desalination systems, which leads to reduce the cost of the system as a whole. Second is the pollution and contamination of water, which raises the cost of the desalination system.
The economics and technical properties of the desalination method with the targeted quantity of freshwater are the factors based on which we select the distillation technique. The technical properties include the energy-driving source, consumed energy, freshwater specifications, land space of unit, station reliability, operational aspects, plant size, and the maintenance of spare parts, while the economic parameters include the fixed costs of the station, operating costs, interest rate, life cycle of station, and maintenance costs …etc. [37]. The cost of distilled freshwater is described by $/m3. The cost of desalinated water is determined using the following equation.
As explained before, solar distillation is one of the desalination techniques. Solar distiller is one of the solar distillation devices’ family. It is a simple in construction, cheap, and easy to maintain device [38]. But it has the demerit of few freshwater production. As a result, the scientists do their best to improve the yield of solar distillers [39, 40, 41, 42, 43, 44, 45]. The solar distiller has the parts of glazing cover, basin, collecting trough, and some instruments as shown in Figures 6 and 7. The basin is fed by saline water to be heated and vaporized inside the distiller. Then, the vapor is condensed on the inner glazing surface. After that, the condensated droplets are taken out using a hose into the calibrated flasks. The surfaces of the solar distiller are painted with black for maximizing the absorbed solar radiations. Also, the device body is insulated by saw dust or fiberglass for avoiding the thermal losses. Moreover, the measuring instruments are utilized to be able to evaluate the solar distiller performance.
Single-basin distiller [
Solar still with simple basin [
One of the biggest problems of the twenty-first century is the global freshwater scarcity, which has numerous side effects on the mankind [47, 48]. The widespread of the water problem on a global level has made more impacts on the lives of people who live far from urbanization and remote areas, and more and more on the lives of the poor who do not have the costs of using high technology to produce water. As a result, the science developed various high and low water desalination technologies to be used at the level of industrial and commercial production and at the level of individuals and families [49]. The water desalination technologies can be categorized by membranes or thermal processes. Nevertheless, the high technologies demand building complex and large central installations, which causes them to be infeasible for developing regions such as distributed, poor, and remote areas. In addition, the rural, arid, and remote areas need desalination methods with no or minimum maintenance, supervising, and operating requirements [41, 45]. Consequently, the solar-powered desalination units such as solar distillers meet all these conditions, which make them as an efficient candidate to provide drinkable water in these regions [42, 43].
Nevertheless, the solar distillers have low output productivity (1.5–2.5 L/m2 day) and low thermal efficiency (≈ 30%), which are the main bottlenecks of this distillation technique [50, 51, 52]. As a result, numerous investigations focused on improving the performance of solar distillers. Consequently, the solar stills such as stepped type [53, 54, 55] (the absorber of the basin takes the steps shape), disk type [56] (the main effective absorber is a rotating disk), vertical type [57] (the distiller horizontal width is very small compared to its vertical height), tubular type [58, 59, 60] (the outer shape of the distiller is tubular/cylindrical), drum type [61, 62] (the absorber is a rotating drum inside the basin still), PV/T active type [63, 64] (distiller powered by PV panels), finned type [65] (the absorber of the distiller is a collection of fins), trays type [66, 67, 68, 69] (the main effective absorber has trays to enlarge the surface area), inclined type [70] (the absorber is inclined), wick type [10, 71, 72] (the wick material is spread over the absorber of distiller), corrugated type [73, 74] (the absorber of the distiller is a collection of corrugated shapes), spherical type [75] (the distiller takes the shape of sphere), double-effect type [76, 77, 78] (the distiller has two stages of water basins), multistage type [79] (the distiller has multistages of water basins), inverted absorber type [80] (the distiller has inverted absorber inside it), hemispherical type [81] (the distiller takes the shape of sphere), convex type [82, 83] (the absorber has a convex shape), and pyramid type [84, 85, 86] (the distiller takes the form of pyramid) are found in the literature. In addition, numerous modifications were performed to improve the distiller performance. These modifications included the use of condensation unit [87, 88, 89], nanofluids [90, 91], heat exchanger [92], floating aluminum sheet [93], desiccant [94], solar ponds [95], glass cooling [44], volcanic rocks [96], wick materials [71], rotating parts [97, 98, 99], coated absorbers [100, 101], phase change materials (PCM) [102, 103, 104], fins [105], half barrel and corrugated absorbers [106], solar collectors [107], sun-tracking systems [108], multiple-effect basins [109], reflectors [110], vapor extraction [111, 112, 113], and reusing latent heat of evaporation [114].
The solar distillers can be classified into single-effect and multi-effect distillers (according to the number of effects of distiller) with a subcategory of active and passive distillers (according to the vaporization heat source) inside every classification [2]. In the passive distillers, the vaporization occurs directly without external sources of heat, while using external heat sources such as collectors and concentrators are used in the active solar distillers.
This is the traditional solar distiller (or conventional distiller) without any modifications [115]. Also, it is used as a reference for the other modified distillers’ performances. Here, in this type of distillers, there is just one glass cover over the basin water. Also, the thermal losses in this type of distiller are large due to the single glass cover, which hence decreases its performance. Therefore, the efficacy of this distiller is low around 30–40% [2]. As a result, numerous experimental and empirical investigations were performed to augment the distiller performance. This type of distillers (single-effect solar distillers) is categorized into active and passive distillers.
The word “active” means that the solar distiller is integrated with somewhat external source of heat such as the solar concentrators and collectors [2]. Then, the active distillers include the following items:
Regenerative distillers
Air bubbled distillers
Waste heat recovery distillers
Distiller with heat exchangers
Distiller integrated with concentrators
Distiller incorporated with hybrid units
Distiller incorporated with heaters
Figure 8 shows the active distiller integrated with evacuated collector.
Active distiller integrated with evacuated collector [
Here, the heat source for basin water vaporization is only from inside of distiller [2]. Then, the passive solar distillers include the following kinds.
Basin distiller (conventional distiller).
Wick distiller.
Weir-type distiller.
Spherical distiller.
Tubular distiller.
Pyramid distiller.
Diffusion distiller.
Greenhouse combination distiller.
Stepped distiller.
For example, Figure 9 obtains a passive distiller incorporated with condenser, and Figure 10 reveals a passive distiller incorporated with internal and external mirrors.
Passive distiller integrated to condenser [
Passive distiller integrated with mirrors: Schematic and photo diagrams [
Multi-effect solar distillers are different in design from the single-basin distillers. Also, the modified design of multi-effect distillers helped enhancing the performance of the distillers. Here, in these types of distillers, the condensation latent heat is utilized as a recovery source of heat to obtain more vaporization through the effect of the distillers, and hence, the freshwater production is augmented [119]. Now, multi-effect solar distillers are categorized into two main sections: active and passive distillers as the following.
It is the same concept of the single-effect distiller. The word “active” means that the solar distiller is integrated with somewhat external source of heat such as the solar concentrators and collectors. Various distiller kinds can be found in the literature under the category of active distiller-based multi-effect distillers.
Multistage evacuated active distiller.
Multi-basin inverted absorber active distiller.
Waste heat recovery active distiller.
Multi-effect condensation–evaporation desalination unit.
Distiller integrated with collectors such as flat plate and tube collector.
A multi-effect active distiller with collector is illustrated in Figure 11. Also, Figure 12 shows a condensation-evaporation active distiller.
Double-effect single-slope active still: a coupled with solar collector in thermosiphon mode and b coupled with solar collector in forced circulation mode [
Condensation–evaporation active distiller [
Here, the passive multi-effect distillers include the following designs of distillers.
Wick distillers.
Conventional distillers.
Weir-type distillers.
Diffusion distillers.
Figure 13 illustrates a passive wick distiller, and Figure 14 shows a double-basin double-effect passive distiller.
Wick-passive distiller [
Double-effect double-basin passive distiller [
Artificial intelligence (AI) is quickly progressing every day. Computers can easily perform the difficult tasks for the humans to do. AI is first contrived in 1950. AI passed with steps and stages; some failed and others succeeded. Deep learning with powerful computers is the main keys of the success of AI. With time, AI can solve numerous industrial problems including the image processing, recognition of speech, language processing, optimization, prediction, robotic automation, categorization, self-driving cars …etc. AI is of numerous branches, and we will focus, in this chapter, on the neural networks (NNs). NNs help the computers to teach themselves from observing the data to predict the system performances. Preparing data for neural network processing is typically the most difficult and time-consuming task you will encounter when working with neural networks. In addition to the enormous volume of data that could easily reach millions and even billions of records, the main difficulty is in preparing the data in the correct format for the task in question.
Contemporary experience indicates that artificial neural networks (ANN’s) may be specifically appropriate to offer tools to assist desalination plant operators in day-to-day operations. Prediction of the productivity of the desalination units is an essential consequence to evaluate its potentiality to provide potable water with involving in conducting more experiments. AI-based methods are stated as robust tools to obtain the correlation between the process parameters and responses [123, 124, 125, 126, 127]. This chapter suggests that ANNs are particularly appropriate as the basis for the development of tools to aid in the various phases of operating a desalination plant. In solar energy applications, different kinds of ANNs predicted and optimized the performance of collectors, cells, distillers, etc. [128]. The most application of ANNs is solving the issues of designing and procedures in electric power systems. Due to the similarities between power plants and desalination plants, the methods of ANNs can be used to predict the performance of desalination plants [129]. The merits of applying ANN included that it handles large amounts of datasets, can discover complex nonlinear relationships among all parameters (dependent and independent), and can find all interactions among all tested parameters.
Zarei and Behyad [130] introduced an ANN to test the effective parameters of the greenhouse on water productivity such as width, length, height of evaporator, and roof transparency. The method obtained an acceptable agreement with the experimental results. Tayyebi and Alishiri [131] used a nonlinear inverse model control strategy based on neural network for predicting the performance of MSF desalination plant. The proposed NNs consisted of three layers identified from input–output data and trained with a descent gradient algorithm. The set point tracking performance of the proposed method was studied when the disturbance is present in MSF unit. Three controllers were provided for checking the saline temperature, last stage level, and salinity. The results obtained that a neural network inverse model control strategy is robust and highly promising to be implemented in such nonlinear systems. An ANN model based on field data was built to investigate the vacuum membrane distillation (VMD) performance at various factors [132]. The introduced model could accurately predict the unseen data of VMD. The correlation coefficient of the overall agreement between ANN predictions and experimental data was found to be more than 0.994. Aish et al. [133] utilized ANN to forecast reverse osmosis performance in Gaza Strip through predicting the next week values of total dissolved solids (TDS) and permeate flow rate of the product water. Multilayer perceptron (MLP) and radial basis function (RBF) neural networks were trained and developed with reference to feedwater parameters including the pressure, pH, and conductivity to predict permeate next week values of flow rate. MLP and RBF neural networks were used for predicting the next week TDS concentrations. Both networks are trained and developed with reference to product water quality variables including the water temperature, pH, conductivity, and pressure. The prediction results showed that both types of neural networks are highly satisfactory for predicting TDS level in the product water quality and satisfactory for predicting permeate flow rate.
Santos et al. [134] simulated the distiller yield based on local weather data such as the solar irradiance, air temperature, glass temperature, and air speed and direction by ANNs. Essa et al. [51] introduced an enhanced ANNs incorporated to Harris Hawks optimizer to anticipate the distiller yield. The optimizer was utilized to get the optimal structure and network factors. Nevertheless, traditional artificial neural networks suffer from trapping in local optima problem during learning process. To overcome this problem, RVFL is proposed as it determines the output weights without involving in time-consuming learning process. Besides, RVFL has a direct connection among the input and output nodes, which is of a substantial impact on the network performance. This aids in avoiding the overfitting issue occurring in other ANNs. Using these merits, the conventional RVFL networks has some restrictions like that there are various conformations can be utilized, and this can affect the quality of water productivity final prediction. Then, Ensemble Random Vector Functional Link Networks (EnsRVFL) [135], which relies on RVFL as a basic modeling, were utilized to eliminate these restrictions of RVFL. A random vector functional link (RVFL) network integrated with artificial ecosystem-based optimization (AEO) algorithm was introduced to predict the seawater greenhouse (SWGH) performance [52]. Power consumption and yield of SWGH were predicted
Based on the above explained sections, the following points can be concluded. The most economic and efficient method to get freshwater is desalination. Demisters are the main component of MSFD technique to prevent mixing the distillate by brine. The thermal performance of MED is better than that of MSFD. For example, GOR is 10 and 15 for MSFD and MED, respectively. RO is considered as the most commercial, economic, and efficient techniques of distillation. The economics and technical properties of the desalination method with the targeted quantity of freshwater are the factors based on which we select the distillation technique. Solar distillers are the simplest and easiest way to get potable water, but they suffer from the few yields. The solar distillers can be classified into single-effect and multi-effect distillers (according to the number of effects of distiller) with a subcategory of active and passive distillers (according to the vaporization heat source) inside every classification.
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\n'}]},successStories:{items:[]},authorsAndEditors:{filterParams:{},profiles:[{id:"396",title:"Dr.",name:"Vedran",middleName:null,surname:"Kordic",slug:"vedran-kordic",fullName:"Vedran Kordic",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/396/images/7281_n.png",biography:"After obtaining his Master's degree in Mechanical Engineering he continued his education at the Vienna University of Technology where he obtained his PhD degree in 2004. He worked as a researcher at the Automation and Control Institute, Faculty of Electrical Engineering, Vienna University of Technology until 2008. His studies in robotics lead him not only to a PhD degree but also inspired him to co-found and build the International Journal of Advanced Robotic Systems - world's first Open Access journal in the field of robotics.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"441",title:"Ph.D.",name:"Jaekyu",middleName:null,surname:"Park",slug:"jaekyu-park",fullName:"Jaekyu Park",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/441/images/1881_n.jpg",biography:null,institutionString:null,institution:{name:"LG Corporation (South Korea)",country:{name:"Korea, South"}}},{id:"465",title:"Dr",name:"Christian",middleName:null,surname:"Martens",slug:"christian-martens",fullName:"Christian Martens",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"479",title:"Dr.",name:"Valentina",middleName:null,surname:"Colla",slug:"valentina-colla",fullName:"Valentina Colla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/479/images/358_n.jpg",biography:null,institutionString:null,institution:{name:"Sant'Anna School of Advanced Studies",country:{name:"Italy"}}},{id:"494",title:"PhD",name:"Loris",middleName:null,surname:"Nanni",slug:"loris-nanni",fullName:"Loris Nanni",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/494/images/system/494.jpg",biography:"Loris Nanni received his Master Degree cum laude on June-2002 from the University of Bologna, and the April 26th 2006 he received his Ph.D. in Computer Engineering at DEIS, University of Bologna. On September, 29th 2006 he has won a post PhD fellowship from the university of Bologna (from October 2006 to October 2008), at the competitive examination he was ranked first in the industrial engineering area. He extensively served as referee for several international journals. He is author/coauthor of more than 100 research papers. He has been involved in some projects supported by MURST and European Community. His research interests include pattern recognition, bioinformatics, and biometric systems (fingerprint classification and recognition, signature verification, face recognition).",institutionString:null,institution:null},{id:"496",title:"Dr.",name:"Carlos",middleName:null,surname:"Leon",slug:"carlos-leon",fullName:"Carlos Leon",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Seville",country:{name:"Spain"}}},{id:"512",title:"Dr.",name:"Dayang",middleName:null,surname:"Jawawi",slug:"dayang-jawawi",fullName:"Dayang Jawawi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Technology Malaysia",country:{name:"Malaysia"}}},{id:"528",title:"Dr.",name:"Kresimir",middleName:null,surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/528/images/system/528.jpg",biography:"K. 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It is also performed as part of surgical protocol during the peri-operative phase in the treatment of peri-implantitis. To date, there is a lack of scientific evidence regarding the additive effect of antibiotics in the treatment of dental implant. This has thus left the clinician with inconclusive recommendations, leading to increase antibiotic prescription. With this increase, the development of antibiotic resistance is becoming a threat to modern healthcare that requires revisiting of current indications and implementation of rational treatment strategies. Therefore, more studies are needed to assess the benefit of antibiotic prescription and whether it is safe to refrain from its use.",book:{id:"5185",slug:"dental-implantology-and-biomaterial",title:"Dental Implantology and Biomaterial",fullTitle:"Dental Implantology and Biomaterial"},signatures:"Dalia Khalil, Bodil Lund and Margareta Hultin",authors:[{id:"179031",title:"Dr.",name:"Dalia",middleName:null,surname:"Khalil",slug:"dalia-khalil",fullName:"Dalia Khalil"},{id:"185113",title:"Dr.",name:"Bodil",middleName:null,surname:"Lund",slug:"bodil-lund",fullName:"Bodil Lund"},{id:"185114",title:"Dr.",name:"Margareta",middleName:null,surname:"Hultin",slug:"margareta-hultin",fullName:"Margareta Hultin"}]},{id:"47915",title:"Rationale for Dental Implants",slug:"rationale-for-dental-implants",totalDownloads:3076,totalCrossrefCites:0,totalDimensionsCites:2,abstract:null,book:{id:"4548",slug:"current-concepts-in-dental-implantology",title:"Current Concepts in Dental Implantology",fullTitle:"Current Concepts in Dental Implantology"},signatures:"Ilser Turkyilmaz and Gokce Soganci",authors:[{id:"171984",title:"Associate Prof.",name:"Ilser",middleName:null,surname:"Turkyilmaz",slug:"ilser-turkyilmaz",fullName:"Ilser Turkyilmaz"}]},{id:"18430",title:"An Important Dilemma in Treatment Planning: Implant or Endodontic Therapy?",slug:"an-important-dilemma-in-treatment-planning-implant-or-endodontic-therapy-",totalDownloads:6264,totalCrossrefCites:0,totalDimensionsCites:0,abstract:null,book:{id:"179",slug:"implant-dentistry-a-rapidly-evolving-practice",title:"Implant Dentistry",fullTitle:"Implant Dentistry - A Rapidly Evolving Practice"},signatures:"Funda Kont Cobankara and Sema Belli",authors:[{id:"28846",title:"Dr.",name:"Funda",middleName:null,surname:"Kont Çobankara",slug:"funda-kont-cobankara",fullName:"Funda Kont Çobankara"},{id:"75862",title:"Prof.",name:"Sema",middleName:null,surname:"Belli",slug:"sema-belli",fullName:"Sema Belli"}]}],onlineFirstChaptersFilter:{topicId:"998",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"81595",title:"Prosthetic Concepts in Dental Implantology",slug:"prosthetic-concepts-in-dental-implantology",totalDownloads:25,totalDimensionsCites:0,doi:"10.5772/intechopen.104725",abstract:"This chapter will address evidence-based prosthetic concepts in dental implantology as well as clinical evidence with focus on appropriate logic and technical skills. Those prosthetic factors are as just important as surgical factors, and long-term success can only be achieved if both of those factors are considered, respected, and strictly followed from planning to prosthetic phase of treatment. This chapter will deal with materials selection for prosthetic part, shape, size, and design of supracrestal parts of abutments and their influence on soft tissue and bone stability around dental implants. Furthermore, one of most important decisions is about choosing the proper way of retention: screw- vs. cement-retained restorations, and it will be discussed in detail. Additionally, emergence profile and its function in soft tissues adaptation and adhesion to different prosthetic materials also have important role in long-term success of dental implant restorations.",book:{id:"10808",title:"Current Concepts in Dental Implantology - From Science to Clinical Research",coverURL:"https://cdn.intechopen.com/books/images_new/10808.jpg"},signatures:"Ivica Pelivan"},{id:"80500",title:"Novel Dental Implants with Herbal Composites: A Review",slug:"novel-dental-implants-with-herbal-composites-a-review",totalDownloads:49,totalDimensionsCites:0,doi:"10.5772/intechopen.101489",abstract:"Missing a permanent tooth is a miserable condition faced by a common man. A tooth decay, periodontitis, mechanical trauma, or any systemic complications lead to such a complication. These bone defects when left untreated lead to severe resorption of the alveolar bone. A proper dental filling with an appropriate bone substitute material could prevent such resorption and paves a way for subsequent implant placement. Dental implants are considered as the prime option by dentists to replace a single tooth or prevent bone resorption. A variety of bone substitutes are available differ in origin, consistency, particle size, porosity, and resorption characteristics. Herbal composites in dentistry fabricated using biphospho-calcium phosphate, casein, chitosan, and certain herbal extracts of Cassia occidentalis, Terminalia arjuna bark, Myristica fragans also were reported to possess a higher ossification property, osteogenic property and were able to repair bone defects. C. occidentalis was reported to stimulate mineralization of the bone and osteoblastic differentiation through the activation of the PI3K-Akt/MAPKs pathway in MC3T3-E1 cells of mice. This implant proved better osteoconductivity and bioactivity compared to pure HAP and other BCP ratios. Terminalia Arjuna was also worked in the incorporation in the graft to enhance the osteogenic property of the implant and gave good results. Another implant bone graft was synthesized containing BCP, biocompatible casein, and the extracts of Myristica fragans and subjected to in vitro investigations and the results revealed the deposition of apatite on the graft after immersing in SBF and also the ALP activity was high when treated with MG-63 cells, NIH-3 T3, and Saos 2 cell lines. This study indicates that the inclusion of plant extract enhances the osteogenic property of the graft. Thus, these novel dental implants incorporated with herbal composites evaluated by researchers revealed an enhanced bone healing, accelerates osseointegration, inhibits osteopenia, and inhibits inflammation. This application of herbal composite inclusion in dentistry and its applications has a greater potential to improve the success rate of dental implants and allows the implications of biotechnology in implant dentistry.",book:{id:"10808",title:"Current Concepts in Dental Implantology - From Science to Clinical Research",coverURL:"https://cdn.intechopen.com/books/images_new/10808.jpg"},signatures:"Gopathy Sridevi and Seshadri Srividya"},{id:"78320",title:"Implant-Retained Maxillary and Mandibular Overdentures - A Solution for Completely Edentulous Patients",slug:"implant-retained-maxillary-and-mandibular-overdentures-a-solution-for-completely-edentulous-patients",totalDownloads:66,totalDimensionsCites:0,doi:"10.5772/intechopen.99575",abstract:"The main goal of modern removable prosthodontics is to restore the normal appearance, function, esthetics and speech in each completely edentulous patient. However, if all teeth are missing in a patient, it becomes very complicated to achieve it using traditional protocols. Therefore, implants were introduced into removable prosthodontics to ensure better retention and stability of the conventional dentures. In case of a large amount of bone missing in the jaw it is necessary to ensure the functioning of the dentures constructing various additional stabilizing and retentive prosthodontic solutions on the osseointegrated implants. Numerous types of attachment systems have been used recently for relating implant-retained overdentures to underlying implants: basically splinting (various bar shape designs) and non-splinting attachments (various ball type attachment, magnet attachment, telescopic coping systems). Indications for their use depend on the surgical and prosthodontic factors such as the number and position of the implants, the amount of free intermaxillary space and the type and size of the overdentures. Different indications, types of the overdentures and the attachment systems will be discussed in this chapter.",book:{id:"10808",title:"Current Concepts in Dental Implantology - From Science to Clinical Research",coverURL:"https://cdn.intechopen.com/books/images_new/10808.jpg"},signatures:"Dubravka Knezović Zlatarić, Robert Ćelić and Hrvoje Pezo"},{id:"79724",title:"Implant Stability Quotient (ISQ): A Reliable Guide for Implant Treatment",slug:"implant-stability-quotient-isq-a-reliable-guide-for-implant-treatment",totalDownloads:60,totalDimensionsCites:0,doi:"10.5772/intechopen.101359",abstract:"Implant stability is a prerequisite for successful dental implants and osseointegration. To determine the status of implant stability, continuous monitoring in an objective and qualitative manner is important. To measure implant stability two different stages are there: Primary and secondary. Primary implant stability at placement is a mechanical phenomenon that is related to the local bone quality and quantity, the type of implant and placement technique used. Primary stability is checked from mechanical engagement with cortical bone. Secondary stability is developed from regeneration and remodeling of the bone and tissue around the implant after insertion and affected by the primary stability, bone formation and remodeling. Implant stability is essential for the time of functional loading. Classical benchmark methods to measure implant stability were radiographs or microscopic analysis, removal torque, push-through and pull-through but due to lack of feasibility, time consumption and ethical reasons other methods have been propounded over period of time like measurement of implant torque, model analysis and most important ISQ which has the ability to monitor osseointegration and the life expectancy of an implant. ISQ is a valuable diagnostic and clinical tool that has far-reaching consequences on implant dentistry and this article throws light on advanced and reliable methods of assessing ISQ.",book:{id:"10808",title:"Current Concepts in Dental Implantology - From Science to Clinical Research",coverURL:"https://cdn.intechopen.com/books/images_new/10808.jpg"},signatures:"Gaurav Gupta"},{id:"79817",title:"Peri-Implant Soft Tissue Augmentation",slug:"peri-implant-soft-tissue-augmentation",totalDownloads:128,totalDimensionsCites:0,doi:"10.5772/intechopen.101336",abstract:"The peri-implant soft tissue (PIS) augmentation procedure has become an integral part of implant-prosthetic rehabilitation. Minimal width of keratinized mucosa (KM) of 2 mm is deemed necessary to facilitate oral hygiene maintenance around the implant and provide hard and soft peri-implant tissue stability. PIS thickness of at least 2 mm is recommended to achieve the esthetic appearance and prevent recessions around implant prosthetic rehabilitation. The autogenous soft tissue grafts can be divided into two groups based on their histological composition—free gingival graft (FGG) and connective tissue graft (CTG). FGG graft is used mainly to increase the width of keratinized mucosa while CTG augment the thickness of PIS. Both grafts are harvested from the same anatomical region—the palate. Alternatively, they can be harvested from the maxillary tuberosity. Soft tissue grafts can be also harvested as pedicle grafts, in case when the soft tissue graft remains attached to the donor site by one side preserving the blood supply from the donor region. Clinically this will result in less shrinkage of the graft postoperatively, improving the outcome of the augmentation procedure. To bypass the drawback connected with FGG or CTG harvesting, substitutional soft tissue grafts have been developed.",book:{id:"10808",title:"Current Concepts in Dental Implantology - From Science to Clinical Research",coverURL:"https://cdn.intechopen.com/books/images_new/10808.jpg"},signatures:"Marko Blašković and Dorotea Blašković"},{id:"79611",title:"Growth Factors and Dental Implantology",slug:"growth-factors-and-dental-implantology",totalDownloads:103,totalDimensionsCites:0,doi:"10.5772/intechopen.101082",abstract:"Normal healing procedure of bone involves various sequential events to develop bone and bridge the bone -to- bone gap. When this healing occurs with a metal (titanium) fixture on one side, it is called as osseointegration. After extensive studies on this topic, it is found that this procedure occurs in presence of various biologic constituents that are spontaneously released at the site. Thus, to accelerate normal healing after implant placement and make results more predictable, it has been proposed to use these autologous factors in the osteotomy site. Since it is the beginning of a new revolution in dental implantology, right now it is essential to analyze all possible combinations of host conditions, bone quality and quantity and bio factors being used. This can definitely be a boon for the patients with compromised systemic or local conditions.",book:{id:"10808",title:"Current Concepts in Dental Implantology - From Science to Clinical Research",coverURL:"https://cdn.intechopen.com/books/images_new/10808.jpg"},signatures:"Deeksha Gupta"}],onlineFirstChaptersTotal:17},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:89,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:32,numberOfPublishedChapters:318,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:141,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:106,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:5,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:15,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. 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Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. He has published more than 100 peer-reviewed research articles and graduated numerous Ph.D. and postdoctoral students.",institutionString:null,institution:{name:"New York University Langone Medical Center",institutionURL:null,country:{name:"United States of America"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:3,paginationItems:[{id:"7",title:"Bioinformatics and Medical Informatics",coverUrl:"https://cdn.intechopen.com/series_topics/covers/7.jpg",isOpenForSubmission:!0,editor:{id:"351533",title:"Dr.",name:"Slawomir",middleName:null,surname:"Wilczynski",slug:"slawomir-wilczynski",fullName:"Slawomir Wilczynski",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000035U1loQAC/Profile_Picture_1630074514792",biography:"Professor Sławomir Wilczyński, Head of the Chair of Department of Basic Biomedical Sciences, Faculty of Pharmaceutical Sciences, Medical University of Silesia in Katowice, Poland. His research interests are focused on modern imaging methods used in medicine and pharmacy, including in particular hyperspectral imaging, dynamic thermovision analysis, high-resolution ultrasound, as well as other techniques such as EPR, NMR and hemispheric directional reflectance. Author of over 100 scientific works, patents and industrial designs. Expert of the Polish National Center for Research and Development, Member of the Investment Committee in the Bridge Alfa NCBiR program, expert of the Polish Ministry of Funds and Regional Policy, Polish Medical Research Agency. Editor-in-chief of the journal in the field of aesthetic medicine and dermatology - Aesthetica.",institutionString:null,institution:{name:"Medical University of Silesia",institutionURL:null,country:{name:"Poland"}}},editorTwo:null,editorThree:null},{id:"8",title:"Bioinspired Technology and Biomechanics",coverUrl:"https://cdn.intechopen.com/series_topics/covers/8.jpg",isOpenForSubmission:!0,editor:{id:"144937",title:"Prof.",name:"Adriano",middleName:"De Oliveira",surname:"Andrade",slug:"adriano-andrade",fullName:"Adriano Andrade",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRC8QQAW/Profile_Picture_1625219101815",biography:"Dr. Adriano de Oliveira Andrade graduated in Electrical Engineering at the Federal University of Goiás (Brazil) in 1997. He received his MSc and PhD in Biomedical Engineering respectively from the Federal University of Uberlândia (UFU, Brazil) in 2000 and from the University of Reading (UK) in 2005. He completed a one-year Post-Doctoral Fellowship awarded by the DFAIT (Foreign Affairs and International Trade Canada) at the Institute of Biomedical Engineering of the University of New Brunswick (Canada) in 2010. Currently, he is Professor in the Faculty of Electrical Engineering (UFU). He has authored and co-authored more than 200 peer-reviewed publications in Biomedical Engineering. He has been a researcher of The National Council for Scientific and Technological Development (CNPq-Brazil) since 2009. He has served as an ad-hoc consultant for CNPq, CAPES (Coordination for the Improvement of Higher Education Personnel), FINEP (Brazilian Innovation Agency), and other funding bodies on several occasions. He was the Secretary of the Brazilian Society of Biomedical Engineering (SBEB) from 2015 to 2016, President of SBEB (2017-2018) and Vice-President of SBEB (2019-2020). He was the head of the undergraduate program in Biomedical Engineering of the Federal University of Uberlândia (2015 - June/2019) and the head of the Centre for Innovation and Technology Assessment in Health (NIATS/UFU) since 2010. He is the head of the Postgraduate Program in Biomedical Engineering (UFU, July/2019 - to date). He was the secretary of the Parkinson's Disease Association of Uberlândia (2018-2019). Dr. Andrade's primary area of research is focused towards getting information from the neuromuscular system to understand its strategies of organization, adaptation and controlling in the context of motor neuron diseases. His research interests include Biomedical Signal Processing and Modelling, Assistive Technology, Rehabilitation Engineering, Neuroengineering and Parkinson's Disease.",institutionString:null,institution:{name:"Federal University of Uberlândia",institutionURL:null,country:{name:"Brazil"}}},editorTwo:null,editorThree:null},{id:"9",title:"Biotechnology - Biosensors, Biomaterials and Tissue Engineering",coverUrl:"https://cdn.intechopen.com/series_topics/covers/9.jpg",isOpenForSubmission:!0,editor:{id:"126286",title:"Dr.",name:"Luis",middleName:"Jesús",surname:"Villarreal-Gómez",slug:"luis-villarreal-gomez",fullName:"Luis Villarreal-Gómez",profilePictureURL:"https://mts.intechopen.com/storage/users/126286/images/system/126286.jpg",biography:"Dr. Luis Villarreal is a research professor from the Facultad de Ciencias de la Ingeniería y Tecnología, Universidad Autónoma de Baja California, Tijuana, Baja California, México. 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He also obtained an MSc in Molecular and Genetic Medicine, and a Ph.D. in Clinical Immunology and Human Genetics from the University of Sheffield, UK. He also completed a short-term fellowship in Pediatric Clinical Immunology and Bone Marrow Transplantation at Newcastle General Hospital, England. Dr. Rezaei is a Full Professor of Immunology and Vice Dean of International Affairs and Research, at the School of Medicine, Tehran University of Medical Sciences, and the co-founder and head of the Research Center for Immunodeficiencies. He is also the founding president of the Universal Scientific Education and Research Network (USERN). Dr. Rezaei has directed more than 100 research projects and has designed and participated in several international collaborative projects. He is an editor, editorial assistant, or editorial board member of more than forty international journals. He has edited more than 50 international books, presented more than 500 lectures/posters in congresses/meetings, and published more than 1,100 scientific papers in international journals.",institutionString:"Tehran University of Medical Sciences",institution:{name:"Tehran University of Medical Sciences",country:{name:"Iran"}}},{id:"180733",title:"Dr.",name:"Jean",middleName:null,surname:"Engohang-Ndong",slug:"jean-engohang-ndong",fullName:"Jean Engohang-Ndong",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/180733/images/system/180733.png",biography:"Dr. Jean Engohang-Ndong was born and raised in Gabon. After obtaining his Associate Degree of Science at the University of Science and Technology of Masuku, Gabon, he continued his education in France where he obtained his BS, MS, and Ph.D. in Medical Microbiology. He worked as a post-doctoral fellow at the Public Health Research Institute (PHRI), Newark, NJ for four years before accepting a three-year faculty position at Brigham Young University-Hawaii. Dr. Engohang-Ndong is a tenured faculty member with the academic rank of Full Professor at Kent State University, Ohio, where he teaches a wide range of biological science courses and pursues his research in medical and environmental microbiology. Recently, he expanded his research interest to epidemiology and biostatistics of chronic diseases in Gabon.",institutionString:"Kent State University",institution:{name:"Kent State University",country:{name:"United States of America"}}},{id:"188773",title:"Prof.",name:"Emmanuel",middleName:null,surname:"Drouet",slug:"emmanuel-drouet",fullName:"Emmanuel Drouet",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/188773/images/system/188773.png",biography:"Emmanuel Drouet, PharmD, is a Professor of Virology at the Faculty of Pharmacy, the University Grenoble-Alpes, France. As a head scientist at the Institute of Structural Biology in Grenoble, Dr. Drouet’s research investigates persisting viruses in humans (RNA and DNA viruses) and the balance with our host immune system. He focuses on these viruses’ effects on humans (both their impact on pathology and their symbiotic relationships in humans). He has an excellent track record in the herpesvirus field, and his group is engaged in clinical research in the field of Epstein-Barr virus diseases. He is the editor of the online Encyclopedia of Environment and he coordinates the Universal Health Coverage education program for the BioHealth Computing Schools of the European Institute of Science.",institutionString:null,institution:{name:"Grenoble Alpes University",country:{name:"France"}}},{id:"131400",title:"Prof.",name:"Alfonso J.",middleName:null,surname:"Rodriguez-Morales",slug:"alfonso-j.-rodriguez-morales",fullName:"Alfonso J. Rodriguez-Morales",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/131400/images/system/131400.png",biography:"Dr. Rodriguez-Morales is an expert in tropical and emerging diseases, particularly zoonotic and vector-borne diseases (especially arboviral diseases). He is the president of the Travel Medicine Committee of the Pan-American Infectious Diseases Association (API), as well as the president of the Colombian Association of Infectious Diseases (ACIN). He is a member of the Committee on Tropical Medicine, Zoonoses, and Travel Medicine of ACIN. He is a vice-president of the Latin American Society for Travel Medicine (SLAMVI) and a Member of the Council of the International Society for Infectious Diseases (ISID). Since 2014, he has been recognized as a Senior Researcher, at the Ministry of Science of Colombia. He is a professor at the Faculty of Medicine of the Fundacion Universitaria Autonoma de las Americas, in Pereira, Risaralda, Colombia. He is an External Professor, Master in Research on Tropical Medicine and International Health, Universitat de Barcelona, Spain. He is also a professor at the Master in Clinical Epidemiology and Biostatistics, Universidad Científica del Sur, Lima, Peru. In 2021 he has been awarded the “Raul Isturiz Award” Medal of the API. Also, in 2021, he was awarded with the “Jose Felix Patiño” Asclepius Staff Medal of the Colombian Medical College, due to his scientific contributions to COVID-19 during the pandemic. He is currently the Editor in Chief of the journal Travel Medicine and Infectious Diseases. His Scopus H index is 47 (Google Scholar H index, 68).",institutionString:"Institución Universitaria Visión de las Américas, Colombia",institution:null},{id:"332819",title:"Dr.",name:"Chukwudi Michael",middleName:"Michael",surname:"Egbuche",slug:"chukwudi-michael-egbuche",fullName:"Chukwudi Michael Egbuche",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/332819/images/14624_n.jpg",biography:"I an Dr. Chukwudi Michael Egbuche. I am a Senior Lecturer in the Department of Parasitology and Entomology, Nnamdi Azikiwe University, Awka.",institutionString:null,institution:{name:"Nnamdi Azikiwe University",country:{name:"Nigeria"}}},{id:"284232",title:"Mr.",name:"Nikunj",middleName:"U",surname:"Tandel",slug:"nikunj-tandel",fullName:"Nikunj Tandel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/284232/images/8275_n.jpg",biography:'Mr. Nikunj Tandel has completed his Master\'s degree in Biotechnology from VIT University, India in the year of 2012. He is having 8 years of research experience especially in the field of malaria epidemiology, immunology, and nanoparticle-based drug delivery system against the infectious diseases, autoimmune disorders and cancer. He has worked for the NIH funded-International Center of Excellence in Malaria Research project "Center for the study of complex malaria in India (CSCMi)" in collaboration with New York University. The preliminary objectives of the study are to understand and develop the evidence-based tools and interventions for the control and prevention of malaria in different sites of the INDIA. Alongside, with the help of next-generation genomics study, the team has studied the antimalarial drug resistance in India. Further, he has extended his research in the development of Humanized mice for the study of liver-stage malaria and identification of molecular marker(s) for the Artemisinin resistance. At present, his research focuses on understanding the role of B cells in the activation of CD8+ T cells in malaria. Received the CSIR-SRF (Senior Research Fellow) award-2018, FIMSA (Federation of Immunological Societies of Asia-Oceania) Travel Bursary award to attend the IUIS-IIS-FIMSA Immunology course-2019',institutionString:"Nirma University",institution:{name:"Nirma University",country:{name:"India"}}},{id:"334383",title:"Ph.D.",name:"Simone",middleName:"Ulrich",surname:"Ulrich Picoli",slug:"simone-ulrich-picoli",fullName:"Simone Ulrich Picoli",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/334383/images/15919_n.jpg",biography:"Graduated in Pharmacy from Universidade Luterana do Brasil (1999), Master in Agricultural and Environmental Microbiology from Federal University of Rio Grande do Sul (2002), Specialization in Clinical Microbiology from Universidade de São Paulo, USP (2007) and PhD in Sciences in Gastroenterology and Hepatology (2012). She is currently an Adjunct Professor at Feevale University in Medicine and Biomedicine courses and a permanent professor of the Academic Master\\'s Degree in Virology. She has experience in the field of Microbiology, with an emphasis on Bacteriology, working mainly on the following topics: bacteriophages, bacterial resistance, clinical microbiology and food microbiology.",institutionString:null,institution:{name:"Universidade Feevale",country:{name:"Brazil"}}},{id:"229220",title:"Dr.",name:"Amjad",middleName:"Islam",surname:"Aqib",slug:"amjad-aqib",fullName:"Amjad Aqib",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/229220/images/system/229220.png",biography:"Dr. Amjad Islam Aqib obtained a DVM and MSc (Hons) from University of Agriculture Faisalabad (UAF), Pakistan, and a PhD from the University of Veterinary and Animal Sciences Lahore, Pakistan. Dr. Aqib joined the Department of Clinical Medicine and Surgery at UAF for one year as an assistant professor where he developed a research laboratory designated for pathogenic bacteria. Since 2018, he has been Assistant Professor/Officer in-charge, Department of Medicine, Manager Research Operations and Development-ORIC, and President One Health Club at Cholistan University of Veterinary and Animal Sciences, Bahawalpur, Pakistan. He has nearly 100 publications to his credit. His research interests include epidemiological patterns and molecular analysis of antimicrobial resistance and modulation and vaccine development against animal pathogens of public health concern.",institutionString:"Cholistan University of Veterinary and Animal Sciences",institution:null},{id:"62900",title:"Prof.",name:"Fethi",middleName:null,surname:"Derbel",slug:"fethi-derbel",fullName:"Fethi Derbel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/62900/images/system/62900.jpeg",biography:"Professor Fethi Derbel was born in 1960 in Tunisia. He received his medical degree from the Sousse Faculty of Medicine at Sousse, University of Sousse, Tunisia. He completed his surgical residency in General Surgery at the University Hospital Farhat Hached of Sousse and was a member of the Unit of Liver Transplantation in the University of Rennes, France. He then worked in the Department of Surgery at the Sahloul University Hospital in Sousse. Professor Derbel is presently working at the Clinique les Oliviers, Sousse, Tunisia. His hospital activities are mostly concerned with laparoscopic, colorectal, pancreatic, hepatobiliary, and gastric surgery. He is also very interested in hernia surgery and performs ventral hernia repairs and inguinal hernia repairs. He has been a member of the GREPA and Tunisian Hernia Society (THS). During his residency, he managed patients suffering from diabetic foot, and he was very interested in this pathology. For this reason, he decided to coordinate a book project dealing with the diabetic foot. Professor Derbel has published many articles in journals and collaborates intensively with IntechOpen Access Publisher as an editor.",institutionString:"Clinique les Oliviers",institution:null},{id:"300144",title:"Dr.",name:"Meriem",middleName:null,surname:"Braiki",slug:"meriem-braiki",fullName:"Meriem Braiki",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/300144/images/system/300144.jpg",biography:"Dr. Meriem Braiki is a specialist in pediatric surgeon from Tunisia. She was born in 1985. She received her medical degree from the University of Medicine at Sousse, Tunisia. She achieved her surgical residency training periods in Pediatric Surgery departments at University Hospitals in Monastir, Tunis and France.\r\nShe is currently working at the Pediatric surgery department, Sidi Bouzid Hospital, Tunisia. Her hospital activities are mostly concerned with laparoscopic, parietal, urological and digestive surgery. She has published several articles in diffrent journals.",institutionString:"Sidi Bouzid Regional Hospital",institution:null},{id:"229481",title:"Dr.",name:"Erika M.",middleName:"Martins",surname:"de Carvalho",slug:"erika-m.-de-carvalho",fullName:"Erika M. de Carvalho",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/229481/images/6397_n.jpg",biography:null,institutionString:null,institution:{name:"Oswaldo Cruz Foundation",country:{name:"Brazil"}}},{id:"186537",title:"Prof.",name:"Tonay",middleName:null,surname:"Inceboz",slug:"tonay-inceboz",fullName:"Tonay Inceboz",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/186537/images/system/186537.jfif",biography:"I was graduated from Ege University of Medical Faculty (Turkey) in 1988 and completed his Med. PhD degree in Medical Parasitology at the same university. I became an Associate Professor in 2008 and Professor in 2014. I am currently working as a Professor at the Department of Medical Parasitology at Dokuz Eylul University, Izmir, Turkey.\n\nI have given many lectures, presentations in different academic meetings. I have more than 60 articles in peer-reviewed journals, 18 book chapters, 1 book editorship.\n\nMy research interests are Echinococcus granulosus, Echinococcus multilocularis (diagnosis, life cycle, in vitro and in vivo cultivation), and Trichomonas vaginalis (diagnosis, PCR, and in vitro cultivation).",institutionString:"Dokuz Eylül University",institution:{name:"Dokuz Eylül University",country:{name:"Turkey"}}},{id:"71812",title:"Prof.",name:"Hanem Fathy",middleName:"Fathy",surname:"Khater",slug:"hanem-fathy-khater",fullName:"Hanem Fathy Khater",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/71812/images/1167_n.jpg",biography:"Prof. Khater is a Professor of Parasitology at Benha University, Egypt. She studied for her doctoral degree, at the Department of Entomology, College of Agriculture, Food and Natural Resources, University of Missouri, Columbia, USA. She has completed her Ph.D. degrees in Parasitology in Egypt, from where she got the award for “the best scientific Ph.D. dissertation”. She worked at the School of Biological Sciences, Bristol, England, the UK in controlling insects of medical and veterinary importance as a grant from Newton Mosharafa, the British Council. Her research is focused on searching of pesticides against mosquitoes, house flies, lice, green bottle fly, camel nasal botfly, soft and hard ticks, mites, and the diamondback moth as well as control of several parasites using safe and natural materials to avoid drug resistances and environmental contamination.",institutionString:null,institution:{name:"Banha University",country:{name:"Egypt"}}},{id:"99780",title:"Prof.",name:"Omolade",middleName:"Olayinka",surname:"Okwa",slug:"omolade-okwa",fullName:"Omolade Okwa",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/99780/images/system/99780.jpg",biography:"Omolade Olayinka Okwa is presently a Professor of Parasitology at Lagos State University, Nigeria. She has a PhD in Parasitology (1997), an MSc in Cellular Parasitology (1992), and a BSc (Hons) Zoology (1990) all from the University of Ibadan, Nigeria. She teaches parasitology at the undergraduate and postgraduate levels. She was a recipient of a Commonwealth fellowship supported by British Council tenable at the Centre for Entomology and Parasitology (CAEP), Keele University, United Kingdom between 2004 and 2005. She was awarded an Honorary Visiting Research Fellow at the same university from 2005 to 2007. \nShe has been an external examiner to the Department of Veterinary Microbiology and Parasitology, University of Ibadan, MSc programme between 2010 and 2012. She is a member of the Nigerian Society of Experimental Biology (NISEB), Parasitology and Public Health Society of Nigeria (PPSN), Science Association of Nigeria (SAN), Zoological Society of Nigeria (ZSN), and is Vice Chairperson of the Organisation of Women in Science (OWSG), LASU chapter. She served as Head of Department of Zoology and Environmental Biology, Lagos State University from 2007 to 2010 and 2014 to 2016. She is a reviewer for several local and international journals such as Unilag Journal of Science, Libyan Journal of Medicine, Journal of Medicine and Medical Sciences, and Annual Research and Review in Science. \nShe has authored 45 scientific research publications in local and international journals, 8 scientific reviews, 4 books, and 3 book chapters, which includes the books “Malaria Parasites” and “Malaria” which are IntechOpen access publications.",institutionString:"Lagos State University",institution:{name:"Lagos State University",country:{name:"Nigeria"}}},{id:"273100",title:"Dr.",name:"Vijay",middleName:null,surname:"Gayam",slug:"vijay-gayam",fullName:"Vijay Gayam",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/273100/images/system/273100.jpeg",biography:"Dr. Vijay Bhaskar Reddy Gayam is currently practicing as an internist at Interfaith Medical Center in Brooklyn, New York, USA. He is also a Clinical Assistant Professor at the SUNY Downstate University Hospital and Adjunct Professor of Medicine at the American University of Antigua. He is a holder of an M.B.B.S. degree bestowed to him by Osmania Medical College and received his M.D. at Interfaith Medical Center. His career goals thus far have heavily focused on direct patient care, medical education, and clinical research. He currently serves in two leadership capacities; Assistant Program Director of Medicine at Interfaith Medical Center and as a Councilor for the American\r\nFederation for Medical Research. As a true academician and researcher, he has more than 50 papers indexed in international peer-reviewed journals. He has also presented numerous papers in multiple national and international scientific conferences. His areas of research interest include general internal medicine, gastroenterology and hepatology. He serves as an editor, editorial board member and reviewer for multiple international journals. His research on Hepatitis C has been very successful and has led to multiple research awards, including the 'Equity in Prevention and Treatment Award” from the New York Department of Health Viral Hepatitis Symposium (2018) and the 'Presidential Poster Award” awarded to him by the American College of Gastroenterology (2018). He was also awarded 'Outstanding Clinician in General Medicine” by Venus International Foundation for his extensive research expertise and services, perform over and above the standard expected in the advancement of healthcare, patient safety and quality of care.",institutionString:"Interfaith Medical Center",institution:{name:"Interfaith Medical Center",country:{name:"United States of America"}}},{id:"93517",title:"Dr.",name:"Clement",middleName:"Adebajo",surname:"Meseko",slug:"clement-meseko",fullName:"Clement Meseko",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/93517/images/system/93517.jpg",biography:"Dr. Clement Meseko obtained DVM and PhD degree in Veterinary Medicine and Virology respectively. He has worked for over 20 years in both private and public sectors including the academia, contributing to knowledge and control of infectious disease. Through the application of epidemiological skill, classical and molecular virological skills, he investigates viruses of economic and public health importance for the mitigation of the negative impact on people, animal and the environment in the context of Onehealth. \r\nDr. Meseko’s field experience on animal and zoonotic diseases and pathogen dynamics at the human-animal interface over the years shaped his carrier in research and scientific inquiries. He has been part of the investigation of Highly Pathogenic Avian Influenza incursions in sub Saharan Africa and monitors swine Influenza (Pandemic influenza Virus) agro-ecology and potential for interspecies transmission. He has authored and reviewed a number of journal articles and book chapters.",institutionString:"National Veterinary Research Institute",institution:{name:"National Veterinary Research Institute",country:{name:"Nigeria"}}},{id:"158026",title:"Prof.",name:"Shailendra K.",middleName:null,surname:"Saxena",slug:"shailendra-k.-saxena",fullName:"Shailendra K. Saxena",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRET3QAO/Profile_Picture_2022-05-10T10:10:26.jpeg",biography:"Professor Dr. Shailendra K. Saxena is a vice dean and professor at King George's Medical University, Lucknow, India. His research interests involve understanding the molecular mechanisms of host defense during human viral infections and developing new predictive, preventive, and therapeutic strategies for them using Japanese encephalitis virus (JEV), HIV, and emerging viruses as a model via stem cell and cell culture technologies. His research work has been published in various high-impact factor journals (Science, PNAS, Nature Medicine) with a high number of citations. He has received many awards and honors in India and abroad including various Young Scientist Awards, BBSRC India Partnering Award, and Dr. JC Bose National Award of Department of Biotechnology, Min. of Science and Technology, Govt. of India. Dr. Saxena is a fellow of various international societies/academies including the Royal College of Pathologists, United Kingdom; Royal Society of Medicine, London; Royal Society of Biology, United Kingdom; Royal Society of Chemistry, London; and Academy of Translational Medicine Professionals, Austria. He was named a Global Leader in Science by The Scientist. He is also an international opinion leader/expert in vaccination for Japanese encephalitis by IPIC (UK).",institutionString:"King George's Medical University",institution:{name:"King George's Medical University",country:{name:"India"}}},{id:"94928",title:"Dr.",name:"Takuo",middleName:null,surname:"Mizukami",slug:"takuo-mizukami",fullName:"Takuo Mizukami",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/94928/images/6402_n.jpg",biography:null,institutionString:null,institution:{name:"National Institute of Infectious Diseases",country:{name:"Japan"}}},{id:"233433",title:"Dr.",name:"Yulia",middleName:null,surname:"Desheva",slug:"yulia-desheva",fullName:"Yulia Desheva",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/233433/images/system/233433.png",biography:"Dr. Yulia Desheva is a leading researcher at the Institute of Experimental Medicine, St. Petersburg, Russia. She is a professor in the Stomatology Faculty, St. Petersburg State University. She has expertise in the development and evaluation of a wide range of live mucosal vaccines against influenza and bacterial complications. 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