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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/52584

Title: Dental diagnosis from X-Ray images: An expert system based on fuzzy computing
Authors: Le Hoang Son
Tran Manh Tuan
Hamido Fujita
Nilanjan Dey
Amira S.Ashour
Vo Truong Nhu Ngoc
Le Quynh Anh
Dinh-Toi Chu
Contributors: 國立臺灣海洋大學:資訊工程學系
Keywords: Dental X-Ray image
Decision making
Graph-based clustering
Medical diagnosis
Semi-Supervised fuzzy clustering
Date: 2018
Issue Date: 2019-11-22T01:23:23Z
Publisher: Biomedical Signal Processing and Control
Abstract: Abstract: Background
Computerized medical diagnosis systems from X-Ray images are of great interest to physicians for accurate decision making of possible diseases and treatments. Subclinical disease has no recognizable clinical findings, thus it is desirable to segment the dental X-Ray image into groups and then use soft computing methods to check the possibility of whether or not any disease occurs therein.

The current work proposed a novel framework called Dental Diagnosis System (DDS) for dental diagnosis based on the hybrid approach of segmentation, classification and decision making. It utilized the best dental image segmentation method based on semi-supervised fuzzy clustering for the segmentation task. A new graph-based clustering algorithm called APC+ for the classification task was proposed. A new decision making procedure was designed to determine the final disease from a group of diseases found from the segments.

The proposed DDS was modeled under the real dental case of Hanoi Medical University, Vietnam including 87 dental images of five popular diseases, namely: root fracture, incluse teeth, decay, missing teeth, and resorption of periodontal bone. The DDS accuracy is 92.74% which is superior to the other methods namely fuzzy inference system (89.67%), fuzzy k-nearest neighbor (80.05%), prim spanning tree (58.46%), kruskal spanning tree (58.46%), and affinity propagation clustering (90.01%).

Empirical results established that superior performance of the DDS to other related methods the findings of the achieved results can assist dental clinicians in their professional work.
Relation: 39 pp.64-73
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/52584
Appears in Collections:[資訊工程學系] 期刊論文

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