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Method and system for multi-organ segmentation using learning-based segmentation and level set optimization

机译:基于学习的分割和水平集优化的多器官分割方法和系统

摘要

A method and system for automatic multi-organ segmentation in a 3D image, such as a 3D computed tomography (CT) volume using learning-base segmentation and level set optimization is disclosed. A plurality of meshes are segmented in a 3D medical image, each mesh corresponding to one of a plurality of organs. A level set in initialized by converting each of the plurality of meshes to a respective signed distance map. The level set optimized by refining the signed distance map corresponding to each one of the plurality of organs to minimize an energy function.
机译:公开了一种用于3D图像中的自动多器官分割的方法和系统,其使用基于学习的分割和水平集优化来进行3D计算机断层摄影(CT)体积。在3D医学图像中分割多个网格,每个网格对应于多个器官之一。通过将多个网格中的每一个转换为各自的有符号距离图来初始化设置的水平。通过细化对应于多个器官中的每个器官的有符号距离图而优化的水平集以最小化能量函数。

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