| Electrical & Electronic Engineering |
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| Automatic segmentation of bladder in CT images |
| Feng SHI, Jie YANG, Yue-min ZHU |
| Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200240, China; CREATIS, INSA of Lyon, University of Lyon 1, Villeurbanne, France |
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Abstract Segmentation of the bladder in computerized tomography (CT) images is an important step in radiation therapy planning of prostate cancer. We present a new segmentation scheme to automatically delineate the bladder contour in CT images with three major steps. First, we use the mean shift algorithm to obtain a clustered image containing the rough contour of the bladder, which is then extracted in the second step by applying a region-growing algorithm with the initial seed point selected from a line-by-line scanning process. The third step is to refine the bladder contour more accurately using the rolling-ball algorithm. These steps are then extended to segment the bladder volume in a slice-by-slice manner. The obtained results were compared to manual segmentation by radiation oncologists. The average values of sensitivity, specificity, positive predictive value, negative predictive value, and Hausdorff distance are 86.5%, 96.3%, 90.5%, 96.5%, and 2.8 pixels, respectively. The results show that the bladder can be accurately segmented.
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Received: 06 March 2008
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