Gallbladder Segmentation in 2-D Ultrasound Images Using Deformable Contour Methods

被引:0
|
作者
Ciecholewski, Marcin [1 ]
机构
[1] Jagiellonian Univ, Inst Comp Sci, PL-30348 Krakow, Poland
关键词
AUTOMATIC SEGMENTATION;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Segmenting the gallbladder from an ultrasonography (US) image allows background elements which are immaterial in the diagnostic process to be eliminated. In this project, several active contour models were used to extract the shape of the gallbladder, both for cases free of lesions, and for those showing specific disease units, namely: lithiasis, polyps, anatomical changes, such as folds or turns of the gallbladder. First, the histogram normalization transformation was executed allowing the contrast of US images to be improved. The approximate edge of the gallbladder was found by applying one of the active contour models like the motion equation, a center-point model or a balloon model. An operation of adding up areas delimited by the determined contours was also executed to more exactly approximate the shape of the gallbladder in US images. Then, the fragment of the image located outside the gallbladder contour was eliminated from the image. The tests conducted have shown that for the 220 US images of the gallbladder, the area error rate (AER) amounted to 16.4%.
引用
收藏
页码:163 / 174
页数:12
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