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基于椭圆描述符分析和改进的种子检测算法的细胞核分割的有效技术。

An efficient technique for nuclei segmentation based on ellipse descriptor analysis and improved seed detection algorithm.

出版信息

IEEE J Biomed Health Inform. 2014 Sep;18(5):1729-41. doi: 10.1109/JBHI.2013.2297030.

Abstract

In this paper, we propose an efficient method for segmenting cell nuclei in the skin histopathological images. The proposed technique consists of four modules. First, it separates the nuclei regions from the background with an adaptive threshold technique. Next, an elliptical descriptor is used to detect the isolated nuclei with elliptical shapes. This descriptor classifies the nuclei regions based on two ellipticity parameters. Nuclei clumps and nuclei with irregular shapes are then localized by an improved seed detection technique based on voting in the eroded nuclei regions. Finally, undivided nuclei regions are segmented by a marked watershed algorithm. Experimental results on 114 different image patches indicate that the proposed technique provides a superior performance in nuclei detection and segmentation.

摘要

在本文中,我们提出了一种有效的方法来分割皮肤组织病理学图像中的细胞核。所提出的技术包括四个模块。首先,它使用自适应阈值技术将细胞核区域从背景中分离出来。接下来,使用椭圆描述符检测具有椭圆形的孤立细胞核。该描述符基于两个椭圆度参数对细胞核区域进行分类。然后,通过基于侵蚀细胞核区域中的投票的改进种子检测技术定位细胞核簇和形状不规则的细胞核。最后,通过标记分水岭算法分割未分裂的细胞核区域。在 114 个不同的图像补丁上的实验结果表明,所提出的技术在细胞核检测和分割方面具有优异的性能。

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