首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >Segmentation of overlapping cells in cervical smears based on spatial relationship and Overlapping Translucency Light Transmission Model
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Segmentation of overlapping cells in cervical smears based on spatial relationship and Overlapping Translucency Light Transmission Model

机译:基于空间关系和重叠半透明光传输模型的宫颈涂片中重叠细胞的分割

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摘要

Overlapping cell segmentation in cervical smear images is a difficult task due to the shape multiformity and color proximity of the cells. In this paper, we propose a segmentation approach by using the spatial relationship of the non-overlapping and overlapping areas as well as Overlapping Translucency Light Transmission Model (OTLTM) to segment the overlapping cells in these images. The spatial relationship, which denotes the overlapping area locates in the middle ground of the non-overlapping areas, reflects the overlapping area can be accurately gained by the precise non-overlapping areas. After removing the background by threshold technique, a fragmentation method by using mean shift and watershed is adopted to divide the overlapping cells into fragments according to the similarity of their colors. The fragments belong to a single-tier individual cell, or to the overlapping area between two cells. We firstly construct the initial fragment collections of non-overlapping areas based on the Voronoi diagram, then the initial collections are optimized by using the initial cell overlapping matrix based on the spatial relationship, and OTLTM based on Beer Lambert law, which states the relationship between the transmittance, attenuation coefficient of a kind of material and the distance the light travels through it. The cell overlapping matrix is accurately reconstructed by the optimized set of the non-overlapping areas. We obtained the segmentation result by combining the cell overlapping matrix and the optimized set of the non-overlapping areas. The experimental results show that the proposed method can give an impressive performance. Besides cervical smear images, these proposed techniques can be utilized in segmenting translucent objects from other kinds of images. (C) 2016 Elsevier Ltd. All rights reserved.
机译:由于细胞的形状多样和颜色接近,在宫颈涂片图像中重叠细胞分割是一项艰巨的任务。在本文中,我们提出了一种利用非重叠和重叠区域的空间关系以及重叠半透明光传输模型(OTLTM)来分割这些图像中重叠单元的分割方法。空间关系表示重叠区域位于非重叠区域的中部,反映出重叠区域可以通过精确的非重叠区域准确获得。通过阈值技术去除背景后,采用均值平移和分水岭的破碎方法,根据重叠细胞的颜色相似性将其划分为碎片。这些片段属于单层单个单元,或者属于两个单元之间的重叠区域。我们首先基于Voronoi图构造非重叠区域的初始片段集合,然后使用基于空间关系的初始细胞重叠矩阵和基于比尔·兰伯特定律的OTLTM来优化初始集合,该关系表示一种材料的透射率,衰减系数以及光通过它的距离。通过优化的非重叠区域集,可以准确地重建单元重叠矩阵。我们通过合并单元重叠矩阵和非重叠区域的优化集来获得分割结果。实验结果表明,该方法具有良好的性能。除了宫颈涂片图像外,这些提议的技术还可以用于分割其他类型图像中的半透明物体。 (C)2016 Elsevier Ltd.保留所有权利。

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