A two-step approach for automatic microscopic image segmentation using fuzzy clustering and neural discrimination

被引：4

作者：

Colantonio S. ^{[1
]}

Salvetti O. ^{[1
]}

Gurevich I.B. ^{[2
]}

机构：

[1] Institute of Information Science and Technologies CNR, 56124 Pisa

[2] Dorodnicyn Computing Center, Russian Academy of Sciences, Moscow 119991

来源：

Pattern Recognition and Image Analysis | 2007年 / 17卷 / 3期

基金：

俄罗斯基础研究基金会;

关键词：

Active Appearance Model; Active Shape Model; Cell Segmentation; Italian National Research Council; Rough Segmentation;

D O I：

10.1134/S1054661807030108

中图分类号：

学科分类号：

摘要：

The early diagnosis of lymphatic system tumors heavily relies on the computerized morphological analysis of blood cells in microscopic specimen images. Automating this analysis necessarily requires an accurate segmentation of the cells themselves. In this paper, we propose a robust method for the automatic segmentation of microscopic images. Cell segmentation is achieved following a coarse-to-fine approach, which primarily consists in the rough identification of the blood cell and, then, in the refinement of the nucleus contours by means of a neural model. The method proposed has been applied to different case studies, revealing its actual feasibility. © 2007 Pleiades Publishing, Ltd.

引用

页码：428 / 437

页数：9

共 18 条

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