A hybrid Fuzzy C-Means and Neutrosophic for jaw lesions segmentation

作     者：Alsmadi, Mutasem K. 

作者机构：Univ Dammam Coll Appl Studies & Community Serv Dept MIS Dammam Saudi Arabia 

出 版 物：《AIN SHAMS ENGINEERING JOURNAL》 (艾因夏姆斯工程杂志)

年 卷 期：2018年第9卷第4期

页      面：697-706页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 

主　　题：Automatic segmentation Jaw panoramic X-ray image Neutrosophy Fuzzy C-Means clustering algorithm 

摘      要：It is really important to diagnose jaw tumor in its early stages to improve its prognosis. A differential diagnosis could be performed using X-ray images;therefore, accurate and fully automatic jaw lesions image segmentation is a challenging and essential task. The aim of this work was to develop a novel, fully automatic and effective method for jaw lesions in panoramic X-ray image segmentation. The hybrid Fuzzy C-Means and Neutrosophic approach is used for segmenting jaw image and detecting the jaw lesion region in panoramic X-ray images which may help in diagnosing jaw lesions. Area error metrics are used to assess the performance and efficiency of the proposed approach from different aspects. Both efficiency and accuracy are analyzed. Specificity, sensitivity and similarity analyses are conducted to assess the robustness of the proposed approach. Comparing the proposed approach with the Hybrid Firefly Algorithm with the Fuzzy C-Means, and the Artificial Bee Colony with the Fuzzy C-Means algorithm, the proposed approach produces the most identical lesion region to the manual delineation by the Oral Pathologist and shows better performance (FP rate is 6.1%, TP rate is 90%, specificity rate is 0.9412, sensitivity rate is 0.9592 and similarity rate is 0.9471). (C) 2016 Ain Shams University.