GrabCut algorithm for dental X-ray images based on full threshold segmentation

作     者：Mao, Jiafa Wang, Kaihui Hu, Yahong Sheng, Weiguo Feng, Qixin 

作者机构：Zhejiang Univ Technol Coll Comp Sci & Technol Hangzhou 310023 Zhejiang Peoples R China Hangzhou Normal Univ Dept Comp Sci Hangzhou 311121 Zhejiang Peoples R China Chinese Acad Sci Xinjiang Inst Ecol & Geog Urumqi 830011 Xinjiang Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China 

出 版 物：《IET IMAGE PROCESSING》 (IET Image Proc.)

年 卷 期：2018年第12卷第12期

页      面：2330-2335页

核心收录：

学科分类：0808[工学-电气工程] 1002[医学-临床医学] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Natural Science Foundation of China [61573316, 61873082] National Key R&D Program of China [2018YFB0204003] 

主　　题：feature extraction biometrics (access control) dentistry medical image processing image segmentation GrabCut algorithm dental X-ray images threshold segmentation high melting point hardness dental biometrics human forensic identification dental-based human identification novel segmentation algorithm difference images complete target tooth image corresponding crown image independent target tooth shape image synthetic image resulted image adjacent dental crowns high segmentation accuracy outline image set median filtering morphological open operation 

摘      要：Teeth are difficult to be destroyed due to their corrosion resistance, high melting point and hardness. Dental biometrics can therefore provide assistance in human forensic identification, especially to the unknown corpses. One of the key issue in dental based human identification is the segmentation of Dental X-ray images. In this paper, a novel segmentation algorithm has been proposed for this purpose. The proposed algorithm is based on full threshold segmentation. We first obtain the outline image set Iwhole(n) and crown image set Icrown(m) of the complete target tooth. Morphological open operation is then applied to the difference images of Iwhole(n) and Icrown(m). Subsequently, the most complete target tooth image and its corresponding crown image are selected. Getting independent target tooth image I-contour and its crown image I-crown from these two images. Median filtering is applied to the synthetic image of I-contour and I-crown, and the resulted image will be used as the Mask for GrabCut to obtain the target tooth image. Experimental results show our proposed algorithm can effectively overcome the problems of uneven grayscale distribution and adhesion of adjacent crowns in dental X-ray images. It can also achieve a high segmentation accuracy and outperform related methods to be compared.