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Learning-based aorta segmentation using an adaptive detach and merge algorithm

机译:使用自适应分离和合并算法的基于学习的主动脉分割

摘要

Systems and methods for segmenting a structure of interest in medical imaging data include generating a binary mask highlighting structures in medical imaging data, the highlighted structures comprising a connected component including a structure of interest. A probability map is computed by classifying voxels in the highlighted structures using a trained classifier. A plurality of detaching operations is performed on the highlighted structures to split the connected component into a plurality of detached connected components. An optimal detaching parameter is determined representing a number of the detaching operations. A detached connected component resulting from performing the number of detaching operations corresponding to the optimal detaching parameter is classified as the structure of interest based on the probability map and the trained classifier.
机译:用于分割医学成像数据中的关注结构的系统和方法包括在医学成像数据中生成二进制掩码突出显示结构,突出显示的结构包括包括感兴趣结构的连接组件。通过使用训练有素的分类器对突出显示的结构中的体素进行分类来计算概率图。在突出显示的结构上执行多个分离操作,以将连接的组件拆分为多个分离的连接的组件。确定代表多个拆卸操作的最佳拆卸参数。基于概率图和训练有素的分类器,将通过执行与最佳拆卸参数相对应的拆卸操作的次数而产生的拆卸的连接部件分类为关注结构。

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