Computer Vision
Bilateral Filtering for Gray and Color Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Effective Segmentation for Dental X-Ray Images Using Texture-Based Fuzzy Inference System
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
A system for human identification from X-ray dental radiographs
Pattern Recognition
Texture analysis of poly-adenylated mRNA staining following global brain ischemia and reperfusion
Computer Methods and Programs in Biomedicine
Technique for preprocessing of digital mammogram
Computer Methods and Programs in Biomedicine
Snakes, shapes, and gradient vector flow
IEEE Transactions on Image Processing
Blood vessel segmentation methodologies in retinal images - A survey
Computer Methods and Programs in Biomedicine
Computer Methods and Programs in Biomedicine
A review of thresholding strategies applied to human chromosome segmentation
Computer Methods and Programs in Biomedicine
Carotid artery image segmentation using modified spatial fuzzy c-means and ensemble clustering
Computer Methods and Programs in Biomedicine
Breast mass contour segmentation algorithm in digital mammograms
Computer Methods and Programs in Biomedicine
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Teeth segmentation for periapical raidographs is one of the most critical tasks for effective periapical lesion or periodontitis detection, as both types of anomalies usually occur around tooth boundaries and dental radiographs are often subject to noise, low contrast, and uneven illumination. In this paper, we propose an effective scheme to segment each tooth in periapical radiographs. The method consists of four stages: image enhancement using adaptive power law transformation, local singularity analysis using Holder exponent, tooth recognition using Otsu's thresholding and connected component analysis, and tooth delineation using snake boundary tracking and morphological operations. Experimental results of 28 periapical radiographs containing 106 teeth in total and 75 useful for dental examination demonstrate that 105 teeth are successfully isolated and segmented, and the overall mean segmentation accuracy of all 75 useful teeth in terms of (TP, FP) is (0.8959, 0.0093) with standard deviation (0.0737, 0.0096), respectively.