Segmentation of confocal microscope images of cell nuclei in thick tissue sections
Segmentation of confocal microscope images of cell nuclei in thick tissue sections
复制标题
DOI：
10.1046/j.1365-2818.1999.00463.x
复制
发表时间：
1999-03-01
影响因子：
2
通讯作者：
Lockett, SJ
中科院分区：
文献类型：
--
作者：
de Solórzano, CO;Rodriguez, EG;Lockett, SJ
从厚组织切片的三维（3D）图像中对完整细胞核进行分割是许多生物学研究所需的一项重要基本能力。然而，由于许多样本类型中细胞核紧密聚集，分割往往很困难。我们提出了一种3D分割方法，它将人类视觉系统的识别能力与自动图像分析算法的效率相结合。该方法首先使用自动算法将3D图像分离为荧光染色细胞核区域和未染色背景区域。这包括一个基于霍夫变换和自动聚焦算法来估计细胞核大小的新步骤。然后，使用交互式显示器将每个核区域展示给分析人员，分析人员将其分类为单个细胞核、多个细胞核的聚集体、部分细胞核或碎片。接下来，基于形态学重建和分水岭算法的自动图像分析将聚集体分割成更小的对象，再由分析人员重新分类。一旦不再有聚集体，分析人员指出哪些部分细胞核应该连接起来形成完整的细胞核。通过计算各种组织类型中正确分割的细胞核比例来评估该方法：秀丽隐杆线虫胚胎（总共848个中839个正确）、正常人皮肤（343/362）、人良性乳腺组织（492/525）、作为小鼠异种移植物生长的人乳腺癌细胞系（425/479）以及浸润性人乳腺癌（260/335）。此外，由于分析人员参与分割过程，假设分析人员的视觉判断正确，那么总是可以知道群体中的哪些细胞核被正确分割，哪些没有。
Segmentation of intact cell nuclei from three-dimensional (3D) images of thick tissue sections is an important basic capability necessary for many biological research studies, However, segmentation is often difficult because of the tight clustering of nuclei in many specimen types. We present a 3D segmentation approach that combines the recognition capabilities of the human visual system with the efficiency of automatic image analysis algorithms. The approach first uses automatic algorithms to separate the 3D image into regions of fluorescence-stained nuclei and unstained background. This includes a novel step, based on the Hough transform and an automatic focusing algorithm to estimate the size of nuclei, Then, using an interactive display each nuclear region is shown to the analyst, who classifies itt as either an individual nucleus, a cluster of multiple nuclei, partial nucleus or debris, next, automatic image analysis based on morphological reconstruction and the watershed algorithm divides clusters into smaller objects, which are reclassified by the analyst. Once no more clusters remain, the analyst indicates which partial nuclei should be joined to form complete nuclei, The approach was assessed by calculating the fraction of correctly segmented nuclei for a variety of tissue types: Caenorhabditis elegans embryos (839 correct out of a total of 848), normal human skin (343/362), benign human breast tissue (492/525), a human breast cancer cell line grown as a xenograft in mice (425/479) and invasive human breast carcinoma (260/335), Furthermore, due to the analyst's involvement in the segmentation process, it is always known which nuclei in a population are correctly segmented and which not, assuming that the analyst's visual judgement is correct.