DocumentCode :
2571806
Title :
An effective approach towards color image segmentation for micro-vessel detection
Author :
Juan Chen ; Quan Wen ; Zhifei Pang ; Mete, Mutlu
Author_Institution :
Sch. of Comput. Sci. & Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
fYear :
2012
fDate :
19-21 Oct. 2012
Firstpage :
59
Lastpage :
63
Abstract :
In this paper, we propose an effective approach towards color image segmentation for micro-vessel detection in the virtual slide of double stained liver tissue. The contribution of the proposed method lies in three aspects. First, the dominant colors of white/gray, blue, red and brown are modeled in the RGB color space. Second, the CART (classification and regress tree) method is implemented to segment the modeled colors. Third, the micro-vessel regions are identified in the color images based on the association of both red and brown pixels. Extensive experiments are carried out to validate the performance of the proposed approach. The experimental results demonstrate that our method is quite promising.
Keywords :
image colour analysis; image segmentation; regression analysis; RGB color space; color image segmentation; double stained liver tissue; microvessel detection; regress tree method; Color; Decision trees; Humans; Image color analysis; Image segmentation; Liver; Tumors; classification and regress tree; color segmentation; double stain; micro-vessel; virtual slide;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Problem-Solving (ICCP), 2012 International Conference on
Conference_Location :
Leshan
Print_ISBN :
978-1-4673-1696-5
Electronic_ISBN :
978-1-4673-1695-8
Type :
conf
DOI :
10.1109/ICCPS.2012.6384283
Filename :
6384283
Link To Document :
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