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The segmentation of MR bladder wall in 3D based on minimum closed set model

机译:基于最小闭合模型的3D膀胱壁的分割

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Efficient and accurate segmentation of bladder wall on MR images is the most challenging part in constructing the virtual cystoscopy. Segmentation results directly affect the subsequent processing. We present an approach of segmenting the bladder wall by solving minimum-cut problem on closure graphs which was firstly used to solve open-pit mining problem. The results were obtained by optimizing the cost functions designed for individual surface and geometric constraints defining the surface smoothness and interaction. This approach yielded precise results in segmenting the inner border of the bladder wall in 2D space, and has the potential to be extended to higher-dimensional space.
机译:MR图像上的膀胱壁的高效和准确分割是构建虚拟膀胱镜检查的最具挑战性的部分。分段结果直接影响随后的处理。我们通过解决首先用于解决露天坑挖掘问题的封闭图来求解膀胱墙来分割膀胱壁的方法。通过优化针对各个表面和几何约束的成本函数来获得结果,可以获得定义表面平滑度和相互作用的各个表面和几何约束。该方法产生精确导致将膀胱壁的内边缘分割在2D空​​间中,并且具有延伸到更高尺寸空间的可能性。

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