脑膜瘤免疫组化图像中增殖细胞和有丝分裂指数的计算机辅助检测

V. Anari, P. Mahzouni, R. Amirfattahi
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引用次数: 21

摘要

ki67标记物染色的脑膜瘤免疫组织化学图像有阳性细胞和阴性细胞。准确计数阳性和阴性细胞的数量对诊断不同类型的脑膜瘤癌起着至关重要的作用。由于脑膜瘤的病理图像包含复杂的细胞簇,准确的细胞计数方法是病理学医师面临的主要挑战。本文提出了一种计算机辅助算法,用于检测脑膜瘤免疫组织化学图像中的增殖细胞和有丝分裂指数。在算法的第一阶段,基于CIElab颜色空间,采用模糊c均值聚类提取正、负细胞;第二阶段采用超侵蚀操作,计数单个细胞和重叠细胞的数量。实验结果表明,该算法能够克服传统方法的一些缺点,并获得病理医师可接受的准确率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computer-aided detection of proliferative cells and mitosis index in immunohistichemically images of meningioma
Immuonohistochemically images of meningioma which are stained by ki67 marker contain positive and negative cells. Accurate counting the number of positive and negative cells in such images play a critical role in diagnosing diffrent type of meningioma cancer. Since pathological images of meningioma contain complex cell cluster accurate cell counting methodology is a major challenge for pathologist physicians. In this paper we provide a computer aided algorithm for detecting proliferative cells and mitosis index in immunohistochemically images of meningioma. In the first stage of the algorithm fuzzy c-means clustering was used to extract positive and negative cells based on CIElab color space. In the second stage, ultraerosion operation was applied to count the number of individual and overlapped cells. Experimental result show that the proposed algorithm is able to overcome some disadvantage of traditional approaches with acceptable accuracy by pathologist physicians.
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