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The purpose of this study is (1) to introduce a new approach for edge detection in orthopantograms (OPGs) and an improved automatic parameter selector for common edge detectors, (2) to present a comparison between our novel approach with common edge detectors and (3) to provide faster outputs without compromising quality. A new approach for edge detection based on statistical measures was introduced: (1) a set of N edge detection results is calculated from a given input image and a selected type of edge detector, (2) N correspondence maps are constructed from N edge detection results, (3) probabilities and average probabilities are computed, (4) an overall correspondence is evaluated for each correspondence map and (5) the correspondence map providing the best overall correspondence is taken as the result of edge detection procedure. A comparison with common edge detectors (the Roberts, Prewitt, Sobel, Laplacian of the Gaussian and Canny methods) with various parameter settings (304 combinations for each test image) was carried out. The methods were assessed objectively [edge mismatch error (EME), modified Hausdorff distance (MHD) and principal component analysis] and subjectively by experts in dentistry and based on time demands. The suitability of the new approach for edge detection in OPGs was confirmed by experts. The current conventional methods in edge detection in OPGs are inadequate (none of the tested methods reach an EME value or MHD value below 0.1). Our proposed approach for edge detection shows promising potential for its implementation in clinical dentistry. It enhances the accuracy of OPG interpretation and advances diagnosis and treatment planning.

The recent progress in understanding the biomedical basis for temporomandibular joint. (TMJ) therapy as well as in computer and imaging technologies is beginning to provide novel insights into TMJ reconstruction, rational diagnostic and therapeutic strategies. Several methods are available for imaging the TMJ. These include basic radiography (such as panorexes and corrected tomograms), ultrasonography, magnetic resonance imaging, and spiral or conebeam computed tomography. The latter technologies allow the joint to be visualized as sections in different planes and can also be rendered as 3 D volumetric reconstructions to enhance diagnostic capabilities. The aim of the study is demonstrate patient's therapy including 1 year recall. This contribution deals with 3D analysis of the mathematical and computer modeling of biomechanics of the jaw. Case report monitors step by step treatment plan, preprosthetic surgery, mandibular reconstruction and process of healing. 3D- CT was used to monitor the patient with dental cysts. The mathematical and computer TMJ models analysis using overlapping of 3D CT before and after 1 year therapy shows the stability of TMJ partial prosthesis reconstruction. Mathematical modeling and mathematical simulation of the reconstruction of patient jaw and/or patient TMJ may predict the joint loading of the reconstructed condyle. Our study demonstrated practical use of 3D images during TMJ therapy. Although many of the disorders involving the temporomandibular joint and associated structures can be diagnosed clinically on the basis of the history and physical findings, there are others that require the use of various imaging techniques to make an accurate diagnosis or to determine the extent of involvement. Imaging the hard and soft tissues of the temporomandibular joint can be used not only for treatment planning but also long-term treatment evaluation.