A Review of Teeth Cancer Using Semi-Supervised Approach
نویسندگان
چکیده
Dental Xray image segmentation (DXIS) is an vitally necessary process in Practical dentistry for diagnosis of periodontitis diseases from an Xray image. DXIS have been investigated to get high accuracy of segmentation. In this paper, we propose a new cooperative scheme that applies semisupervised Fuzzy clustering algorithm to DXIS. Specifically, the Otsu method is used to remove the Background area from an Xray dental image. The FCM algorithm is chosen to remove the Dental Structure area from the results of the previous steps. Atlast, Semi-supervised Entropy regularized Fuzzy Clustering algorithm (eSFCM) is opted to clarify and improve the results. The proposed framework is evaluated on a real collection of dental X-ray image dataset. The usefulness and significance of this research are fully demonstrated within the extent of real-life
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