DocumentCode :
2480887
Title :
Segmentation of medical images with Canny operator and GVF snake model
Author :
Cheng, Jinyong ; Xue, Ruojuan ; Lu, Wenpeng ; Jia, Ruixiang
Author_Institution :
Sch. of Inf. Sci. & Technol., Shandong Inst. of Light Ind., Jinan
fYear :
2008
fDate :
25-27 June 2008
Firstpage :
1777
Lastpage :
1780
Abstract :
In computer vision, edge detection is a hot research area in which Canny operator is a typical algorithm. Canny operator has preferable anti-noise ability. However the edge based on Canny operator is not consecutive. GVF snake model is used widely in image segmentation. But there are problems in convergence processing to boundaries of some medical image because of noise. This paper presents a new segmentation algorithm to medical image. First, rough edge is got by Canny operator, and then thinning method based on mathematical morphology is adopted to get edge map as foundation of GVF snake model. This method solves the problem that the edge based on Canny operator is not consecutive. And it improves GVF Snake modelpsilas anti-noise ability. Experiments indicate that the new algorithm can improve snake modelpsilas ability to segment the complicated image.
Keywords :
computer vision; convergence; edge detection; gradient methods; image denoising; image segmentation; image thinning; mathematical morphology; medical image processing; vectors; Canny operator; antinoise ability; computer vision; convergence processing; edge detection; gradient vector flow snake model; mathematical morphology; medical image segmentation; thinning method; Active contours; Biomedical image processing; Biomedical imaging; Computer industry; Deformable models; Humans; Image edge detection; Image segmentation; Industrial control; Morphology; Canny operator; Image segmentation; gradient vector flow; medical image processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
Type :
conf
DOI :
10.1109/WCICA.2008.4593191
Filename :
4593191
Link To Document :
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