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Epithelial Area Detection in Cytokeratin Microscopic Images Using MSER Segmentation in an Anisotropic Pyramid

机译:各向异性金字塔中使用MSER分割的细胞角蛋白显微图像中的上皮区域检测

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摘要

The objective of semantic segmentation in microscopic images is to extract the cellular, nuclear or tissue components. This problem is challenging due to the large variations of features of these components (size, shape, orientation or texture). In this paper we present an automatic technique to robustly delimit the epithelial area (crypts) in microscopic images taken from colon tissues sections marked with cytokeratin-8. The epithelial area is highlighted using the anisotropic diffusion pyramid and segmented using MSER+. The crypts separation and lumen detection is performed by imposing topological constraints about the epithelial layer distribution within the tissue and the round-like shape of the crypt. The evaluation of the proposed method is made by comparing the results with ground-truth segmentations.
机译:显微图像中语义分割的目的是提取细胞,核或组织成分。由于这些组件的特征(大小,形状,方向或纹理)的巨大差异,因此此问题具有挑战性。在本文中,我们提出了一种自动技术,用于从标有cytokeratin-8标记的结肠组织切片中拍摄的显微图像中可靠地划定上皮区域(隐窝)。上皮区域使用各向异性扩散金字塔突出显示,并使用MSER +进行分割。隐窝分离和管腔检测是通过对组织内的上皮层分布和隐窝的圆形形状施加拓扑约束来执行的。通过将结果与地面真假分割进行比较,对所提出的方法进行了评估。

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