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

机译:二维超声图像中可变形轮廓法对胆囊分割

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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%.
机译:从超声(US)图像中分割胆囊可以消除在诊断过程中不重要的背景元素。在该项目中,使用了几个活动轮廓模型来提取胆囊的形状,无论是无病变的病例,还是表现出特定疾病单位的病例,即:结石,息肉,解剖学变化(例如胆囊的褶皱或转弯) 。首先,执行直方图归一化转换,可以改善US图像的对比度。通过应用活动轮廓模型(例如运动方程式,中心点模型或气球模型)之一,可以找到胆囊的近似边缘。还执行了将确定的轮廓所界定的区域相加的操作,以更精确地近似美国图像中的胆囊形状。然后,从图像中消除了位于胆囊轮廓之外的图像片段。进行的测试表明,对于220幅美国胆囊图像,区域错误率(AER)总计为16.4%。

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