DocumentCode :
1564932
Title :
Segmentation of the Left Venctricle from MR Images via Snake Models Incorporating Shape Similarities
Author :
Yuanquan Wang ; Yunde Jia
Author_Institution :
Sch. of Comput. Sci., Beijing Inst. of Technol., China
fYear :
2006
Firstpage :
213
Lastpage :
216
Abstract :
Magnetic resonance imaging is a noninvasive method to measure the geometry and deformation of the heart during one cardiac cycle. To make thorough use of this anatomical and functional information, it is necessary to segment the endo- and epicardium of the left ventricle. In this study, we present a method based on GVF snake model for this purpose. For endocardium segmentation, the proposed method pays particular attention to papillary muscle and artifacts by adopting a shape energy, with this energy, the snake contour can overcome the spurious edges stemming from artifacts and the final results could depend much less on the initial contour. In order to segment the epicardium, a novel energy based on shape similarity is proposed by assuming that the epicardium resembles the endocardium in shape. In addition, a new strategy is developed to derive the external force. This new force can push the snake contour directly to the epicardium when using the endocardium as initialization. By applying the proposed method to a set of 140 cardiac images, its accuracy and robustness is demonstrated and validated.
Keywords :
biomechanics; biomedical MRI; blood vessels; cardiovascular system; computational geometry; gradient methods; image segmentation; medical image processing; muscle; vectors; anatomical information; cardiac MR images; cardiac cycle; endocardium segmentation; epicardium segmentation; gradient vector flow snake contour models; heart deformation; heart functional information; heart geometry; image artifacts; left ventricle; magnetic resonance imaging; noninvasive method; papillary muscle; shape similarities; Active contours; Deformable models; Image segmentation; Level set; Magnetic resonance imaging; Muscles; Parameter estimation; Robustness; Shape measurement; Solid modeling; GVF Snake; Left Ventricle; Segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2006 IEEE International Conference on
Conference_Location :
Atlanta, GA
ISSN :
1522-4880
Print_ISBN :
1-4244-0480-0
Type :
conf
DOI :
10.1109/ICIP.2006.312458
Filename :
4106504
Link To Document :
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