Electromagnetic waves at microwave frequencies allow penetration into many optically non-transparent mediums such as biological tissues. Over the past 30 years, researchers have extensively investigated microwave imaging (MI) approaches including imaging algorithms, measurement systems and applications in biomedical fields, such as breast tumor detection, brain stroke detection, heart imaging and bone imaging. Successful clinical trials of MI for breast imaging brought worldwide excitation, and this achievement further confirmed that the MI has potential to become a low-risk and cost-effective alternative to existing medical imaging tools such as X-ray mammography for early breast cancer detection. This chapter offers comprehensive descriptions of the most important MI approaches for early breast cancer detection, including reconstruction procedures and measurement systems as well as apparatus.
Part of the book: Breast Imaging
Early cancer detection and suitable treatment improve the 5-year survival rates of lung cancer significantly. Many cancer diagnostic approaches have been investigated, including mammography, magnetic resonance imaging, ultrasound, computerized tomography, positron emission tomography and biopsy. However, these techniques have some drawbacks such as expensive and time-consuming. Electromagnetic tomography (EMT) has been proposed as a promising diagnostic tool for lung cancer detection. In addition, developing label-free and cost-effective biosensors for target tumor markers detection have attracted attentions worldwide. This chapter reviews the recently developed EMT and bio-sensing techniques for early-stage lung cancer detection.
Part of the book: State of the Art in Nano-bioimaging
This chapter investigates the feasibility of using 3D holographic millimeter-wave (HMMW) imaging for diagnosis of concealed metallic forging objects (MFOs) in inhomogeneous medium. A 3D numerical system, including radio frequency (RF) transmitters and detectors, various realistic MFOs models and signal and imaging processing, is developed to analyze the measured data and reconstruct images of target MFOs. Simulation and experimental validations are performed to evaluate the HMMW approach for diagnosis of concealed MFOs. Results show that various concealed objects can be clearly represented in the reconstructed images with accurate sizes, locations and shapes. The proposed system has the potential for further investigation of concealed MFOs under clothing in the future, which has the potential applications in on body concealed weapon detection at security sites or MFOs detection in children.