Hand radiograph image segmentation using a coarse-to-fine strategy

被引:17
|
作者
Han, Chin-Chuan [1 ]
Lee, Chang-Hsing
Peng, Wen-Li
机构
[1] Natl United Univ, Dept Comp Sci & Informat Engn, Miaoli, Taiwan
[2] Chung Hua Univ, Dept Comp Sci & Informat Engn, Hsinchu, Taiwan
关键词
bone age assessment; watershed transform; active contour model; metaphyseal/epiphyseal region; gradient vector flow;
D O I
10.1016/j.patcog.2007.01.010
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Image segmentation techniques have been widely applied in diagnosis systems with medical image support. Information about metaphyseal and epiphyseal regions is crucial in bone age assessment. In this study, hand radiograph images have been segmented using a coarse-to-fine strategy. Watershed transform is first done to get metaphyseal regions at a coarse level. Some image processing algorithms, such as noise removal, labeling, and ellipse region fitting, are performed to find the epiphyseal regions of interest (ROIs). The epiphyseal regions are extracted using an active contour model approach based on GVF (gradient vector flow) at a fine level. Some hand radiograph images are processed to show the validity of the proposed approach. (c) 2007 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:2994 / 3004
页数:11
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