期刊
PATTERN RECOGNITION
卷 42, 期 6, 页码 1104-1112出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.patcog.2008.07.007
关键词
Cancer detection; Image segmentation; Histopathological image analysis; Object-oriented texture; Colon adenocarcinoma
资金
- Scientific and Technological Research Council of Turkey [TUBITAK 106E118]
Staining methods routinely used in pathology lead to similar color distributions in the biologically different regions of histopathological images. This causes problems in image segmentation for the quantitative analysis and detection of cancer. To overcome this problem, unlike previous methods that use pixel distributions, we propose a new homogeneity measure based on the distribution of the objects that we define to represent tissue components. Using this measure, we demonstrate a new object-oriented segmentation algorithm. Working with colon biopsy images, we show that this algorithm segments the cancerous and normal regions with 94.89 percent accuracy on the average and significantly improves the segmentation accuracy compared to its pixel-based counterpart. (C) 2008 Elsevier Ltd. All rights reserved.
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