The integration of image processing in novel systems bids fair to significantly improve the endodontic practice in the near future. Also, the attempt to automatically locate and classify the root canals may result in significantly decreased chair time for both the patient and the practitioner. We focus on the shapes of human root canals and their automatic classification, methods for automatic processing, and center line identification of tooth root canal as defined previously. We introduce some micro-computed tomography image analysis methods possible for clinical implementation of cone beam computed tomography image analysis in endodontics and limitations of novel techniques. In this chapter, we present our results of segmentation and root canal identification of cone beam computed tomography images.
Part of the book: Computer Vision in Dentistry
The daily application of cone-beam computed tomography (CBCT) has been increasing. Not only the number of referrals has been raising, but also the variety of the anatomical regions requested for imaging is also growing in the dentomaxillofacial area. Even though computed tomography (CT) has been widely used in the head and neck region, by the invention of CBCT, some of the drawbacks of CT were overcome and turned into the advantages of the CBCT appliances, such as lower patient dose. In this chapter, we provide a comprehensive picture of the everyday use of CBCT as a modality in the dentomaxillofacial region and its current limitations and expected improvements.
Part of the book: Novel Imaging and Spectroscopy