Automatic segmentation of bladder and prostate using coupled 3D deformable models
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
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The radiotherapy treatment planning requires the delineation of the therapy structures that will be submitted to the radiation beams. When executed manually, this delineation is a slow process and can result in human errors due to the amount of X-ray Computed Tomography (CT) images that are analyzed in each radiotherapy planning. This process needs precision, minimizing the radiation on healthy areas, close to the target tissues. A new system for automatic segmentation of images of clinical structures is proposed in this work. The algorithm is based on multi-region growing followed by watershed transform. The main contributions are the method of seed pixels selection and predicate of the multi-region growing algorithm and the segmentation results achieved. The system was tested in 400 images and its efficiency was measured by two different statistical methods, correlation and the t-test. The clinical structures of interest are the rectum, bladder and seminal vesicles.