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Brain tumor vascular network segmentation from micro-tomography

机译:显微断层摄影术对脑肿瘤血管网络的分割

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Micro-tomography produces high resolution images of biological structures such as vascular networks. In this paper, we present a new approach for segmenting vascular network into pathological and normal regions from considering their micro-vessel 3D structure only. We define and use a conditional random field for segmenting the output of a watershed algorithm. The tumoral and normal classes are thus characterized by their respective distribution of watershed region size interpreted as local vascular territories.
机译:显微断层扫描可产生高分辨率的生物结构图像,例如血管网络。在本文中,我们提出了一种仅考虑微血管3D结构就将血管网络划分为病理区域和正常区域的新方法。我们定义并使用条件随机字段来分割分水岭算法的输出。因此,肿瘤和正常类别的特征是它们各自的分水岭区域大小分布被解释为局部血管区域。

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