Snake Model-Based Automatic Segmentation of the Left Ventricle from Cardiac MR Images

Author

Wu, Yuwei ; Wang, Yuanquan ; Lu, Kun

Author_Institution

Beijing Lab. of Intell. Inf. Technol., Beijing Inst. of Technol., Beijing, China

fYear

2009

fDate

17-19 Oct. 2009

Firstpage

1

Lastpage

5

Abstract

An approach based on selective smoothing direction gradient vector flow (SSDGVF) snake model incorporating shape prior is proposed to segment the left ventricle from cardiac MR images in this paper. The originalities of the presented method include SSDGVF algorithm, automatic localization of the cardiac endocardium contour, and elliptic shape constraint. This novel approach can overcome the unexpected local minimum, and conquer the weak boundary leakage in tracking the boundaries of the left ventricle myocardium. Validation is performed on a set of 21 cardiac MR images, and satisfactory segmentation results are obtained.

Keywords

biomedical MRI; cardiology; image segmentation; medical image processing; muscle; automatic localization; cardiac MR images; cardiac endocardium contour; elliptic shape constraint; image segmentation; left ventricle myocardium; selective smoothing direction gradient vector flow snake model; snake model-based automatic segmentation; Active contours; Anisotropic magnetoresistance; Image edge detection; Image segmentation; Information technology; Level set; Myocardium; Noise robustness; Shape; Smoothing methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Engineering and Informatics, 2009. BMEI '09. 2nd International Conference on

Conference_Location

Tianjin

Print_ISBN

978-1-4244-4132-7

Electronic_ISBN

978-1-4244-4134-1

Type

conf

DOI

10.1109/BMEI.2009.5305142

Filename

5305142