首页> 外文会议>International Workshop on Computer Vision for Biomedical Image Applications(CVBIA 2005); 20051021; Beijing(CN) >Constrained Surface Evolutions for Prostate and Bladder Segmentation in CT Images
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Constrained Surface Evolutions for Prostate and Bladder Segmentation in CT Images

机译:CT图像中前列腺和膀胱分割的受约束表面演变

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We propose a Bayesian formulation for coupled surface evolutions and apply it to the segmentation of the prostate and the bladder in CT images. This is of great interest to the radiotherapy treatment process, where an accurate contouring of the prostate and its neighboring organs is needed. A purely data based approach fails, because the prostate boundary is only partially visible. To resolve this issue, we define a Bayesian framework to impose a shape constraint on the prostate, while coupling its extraction with that of the bladder. Constraining the segmentation process makes the extraction of both organs' shapes more stable and more accurate. We present some qualitative and quantitative results on a few data sets, validating the performance of the approach.
机译:我们提出了一种用于耦合表面演化的贝叶斯公式,并将其应用于CT图像中的前列腺和膀胱的分割。这对于放射疗法的治疗过程非常感兴趣,在该过程中,需要对前列腺及其邻近器官进行精确的轮廓绘制。单纯基于数据的方法失败了,因为前列腺边界仅部分可见。为了解决这个问题,我们定义了一个贝叶斯框架以在前列腺上施加形状约束,同时将其提取与膀胱的提取耦合。限制分割过程使提取两个器官的形状更加稳定和准确。我们在一些数据集上给出了一些定性和定量结果,验证了该方法的性能。

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