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首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >An efficient method based on watershed and rule-based merging for segmentation of 3-D histo-pathological images
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An efficient method based on watershed and rule-based merging for segmentation of 3-D histo-pathological images

机译:一种基于分水岭和基于规则的合并的有效方法来分割3D组织病理图像

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摘要

This paper deals with the segmentation of 3-D histo-pathological images. Here we have presented a region-based segmentation method involving watershed algorithm and the rule-based merging technique. We have implemented a new method similar to flooding process for circumventing the inability to automatically mark the regional minima in small isolated objects. The 3-D histo-pathological images for testing the algorithm are obtained using confocal microscope in the form of a stack of optical sections. Normally, result of a classical watershed algorithm on grey-scale textured images such as tissue images is over-segmentation. We have proposed a rule-based heuristic merging technique to reduce the over-segmentation of cells. The lilly fragments of the cells and their parents are identified based on some heuristic rules and are merged together. Rule-based merging gives more than 90% accurate segmentation when compared to simple classical watershed extended to 3-D. Results are shown on 3-D images of prostate cancer tissue specimen. (C) 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved. [References: 26]
机译:本文涉及3-D组织病理学图像的分割。在这里,我们提出了一种基于区域的分割方法,涉及分水岭算法和基于规则的合并技术。我们实施了一种类似于淹没过程的新方法,来规避无法自动标记小的孤立对象中的区域最小值的方法。使用共聚焦显微镜以光学切片的形式获得用于测试算法的3D组织病理学图像。通常,对诸如组织图像之类的灰度纹理图像进行经典分水岭算法的结果是过度分割。我们提出了一种基于规则的启发式合并技术,以减少单元格的过度分割。根据一些启发式规则确定细胞的礼来碎片及其亲本,并将其融合在一起。与扩展到3-D的简单经典分水岭相比,基于规则的合并可提供90%以上的精确分割。结果显示在前列腺癌组织标本的3D图像上。 (C)2001模式识别学会。由Elsevier Science Ltd.出版。保留所有权利。 [参考:26]

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