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Crypts detection in microscopic images using hierarchical structures

机译:使用分层结构的显微图像中的隐窝检测

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This paper presents an extended and improved version of an automatic technique which robustly identifies the epithelial nuclei (crypt) against interstitial nuclei in microscopic images taken from colon tissues. The detection of the crypt inner boundary is performed using the closing morphological hierarchy. The disadvantages of this approach related to the execution time and the used memory are highlighted and the morphological pyramid is used instead due to its computational efficiency, the reduced amount of used memory and the increased robustness. An analysis of the two approaches is performed considering the number of processed pixels, the used memory and the complexity. The outer border is determined by the epithelial nuclei overlapped by the maximal isoline of the inner boundary. The percentage of the mis-segmented nuclei against epithelial nuclei per crypt is used to evaluate the proposed methods. The limitations are described in order to highlight the situations in which the current approaches do not provide suitable results.
机译:本文提出了一种自动技术的扩展和改进版本,该技术可从结肠组织拍摄的显微图像中可靠地识别上皮细胞核(隐窝)以对抗间质细胞核。隐窝内部边界的检测是使用闭合形态层次进行的。强调了这种方法与执行时间和使用的内存有关的缺点,并且由于其计算效率,减少的使用内存量和增强的鲁棒性而使用了形态金字塔。考虑到处理的像素数,使用的内存和复杂性,对这两种方法进行了分析。外边界由与内边界的最大等值线重叠的上皮细胞核决定。每个隐窝相对于上皮核错节的核的百分比用于评估所提出的方法。描述这些限制是为了突出当前方法无法提供合适结果的情况。

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