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Multi-atlas based segmentation of human cerebellum

机译:基于人体小脑的多标准率分割

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Atlas-based segmentation is a high-level technique which provides highly accurate results particularly in the anatomical segmentation of medical images. The main idea of this technique consists in using a dataset of atlases which is perceived as a priori information necessary for providing the automatic segmentation of images. In the current state of the art of atlas-based techniques, the segmentation task is carried out based on a fixed database of atlases. In this article, we propose a multi-atlas segmentation method for brain MRI images based on a dynamic atlas database which is progressively updated each time a new case is added. The experiments show that the suggested technique seems to perform well compared to conventional multi-atlas based segmentation methods.
机译:基于地图集的分割是一种高级技术,它提供了高精度的结果,特别是在医学图像的解剖分割中。该技术的主要思想包括使用atlase的数据集,该数据集被认为是提供自动分割图像所必需的先验信息。在基于地图集的技术领域的当前状态下,基于固定的atlase数据库执行分割任务。在本文中,我们提出了一种基于动态地图集数据库的脑MRI图像的多标准分割方法,每次添加新案例时逐渐更新。实验表明,与基于常规的多标准的分段方法相比,该建议的技术似乎表现良好。

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