水平集法在无线胶囊内镜下小肠肿瘤分割中的应用

M. Alizadeh, H. Soltanian-Zadeh, O. H. Maghsoudi
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引用次数: 20

摘要

在本文中,我们提出了一种分割小肠肿瘤的算法。为了提高水平集方法(LSM)的有效性,我们采用了基于图像光照先验信息的自适应伽玛校正方法(AGCM)。我们将这种方法应用于无线胶囊内窥镜(WCE)拍摄的10张小肠肿瘤图像。在AGCM的不同参数(0.05、0.07、0.09、0.11和0.13)下,计算了手磨法的灵敏度、特异度和准确度,并与传统LSM和Snake法进行了比较。在a=0.13时,该方法的灵敏度提高到0.87,而其他性能测量值随着a的增加而降低,其他方法的灵敏度分别为0.2和0.22。这些测量的最佳值是0.73,发生在a=0.1中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Segmentation of Small Bowel Tumors in Wireless Capsule Endoscopy Using Level Set Method
In this paper, we proposed an algorithm to segment small bowel tumors. In order to increase effectiveness of Level Set Method (LSM) we applied adaptive gamma correction method (AGCM) that is based on prior information of illumination of images. We applied this method on 10 small bowel tumor images captured by Wireless Capsule Endoscopy (WCE). The performance measurements (i.e. sensitivity, specificity, and accuracy) by using hand ground method are computed for different parameters of a (0.05, 0.07, 0.09, 0.11, and 0.13) in AGCM, and then compared with traditional LSM and Snake method. The proposed method shows increased sensitivity up to 0.87 in a=0.13 while other performance measurements decrease by increasing value of a. the sensitivity of the other methods are 0.2 and 0.22, respectively. The optimal value of these measurements is 0.73 that takes place in a=0.1.
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