The segmentation of bladder cancer using the voxel-features-based method

摘要

Accurate segmentation of bladder cancer is the basis for determining the staging of bladder cancer. In our previous study,we have segmented the inner and outer surface of bladder wall and obtained the candidate region of bladder cancer,however, it is hard to segment the cancer region from the candidate region. To segment the cancer region accurately, weproposed a voxel-feature-based method and extracted 1159 features from each voxel of candidate region. After featureextraction, the recursive feature elimination-based support vector machine classifier (SVM-RFE) method was adopted toobtain an optimal feature subset for the classification of the cancer and the wall regions. According to feature selectionand ranking, 125 top-ranked features were selected as the optimal subset, with an area under the receiver operatingcharacteristic curve, accuracy, sensitivity, and specificity of 1, 99.99%, 99.98%, and 1. Using the optimal subset, wecalculated the probability value of each voxel belonging to the cancer region, then obtained the boundary to separate thetumor and wall regions. The mean DSC of the segmentation results in the testing set is 0.9127, indicating that theproposed method can accurately segment the bladder cancer region.