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结合水平集方法和形状约束Snake模型的左心室MRI图像分割*

, PP. 782-786

Keywords: Snake模型,水平集方法,形状约束能量,左心室分割,MRI图像

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Abstract:

提出结合水平集方法和形状约束Snake模型的左心室MRI图像分割算法.由于左心室存在弱边缘、与周围的组织之间存在低对比度区域,Snake模型分割左心室MRI图像时,将会出现变形曲线泄漏现象.通过对训练图像的配准、变化模式的分析,定义左心室的边界形状变化允许空间.根据心脏MRI图像的特点,使用水平集方法在平均形状周围构造形状约束能量场.在Snake模型中增加形状约束能量项后,能够有效处理变形曲线的泄漏问题.通过将演化曲线投影到形状允许空间,对其施加形状约束.心脏MRI图像的分割实验证明了模型的有效性.

References

[1]  Kass M, Witkin A, Terzopoulos D. Snake: Active Contour Models. International Journal of Computer Vision, 1988, 1 (4):321-331
[2]  Lin Yao, Tian Jie. A Review on Segmentation Methods of Medical Images. Pattern Recognition and Artificial Intelligence, 2002, 15(2):192-204 (in Chinese) (林 瑶,田 捷.医学图象分割方法综述.模式识别与人工智能, 2002, 15(2): 192-204)
[3]  Amini A A, Weymouth T E, Jain T C. Using Dynamic Programming for Solving Variational Problems in Vision. IEEE Trans on Pattern Analysis and Machine Intelligence, 1990, 12 (9): 855-867
[4]  Cohen L D. On Active Contour Models and Balloons. Computer Vision, Graphics and Image Processing: Image Understanding, 1991, 53(2): 211-218
[5]  Xu C, Prince J L. Snakes, Shapes and Gradient Vector Flow. IEEE Trans on Image Processing, 1998, 7(3): 359-369
[6]  Zhou Zeming, Wang Yuanquan, Pheng A H, et al. 3D Left Ventricle Surface Reconstruction Based on Level Sets. Journal of Computer Research and Development, 2005, 42(7): 1173-1178 (in Chinese) (周则明,王元全,王平安,等. 基于水平集的3D左心室表面重建.计算机研究与发展, 2005, 42(7): 1173- 1178)
[7]  Steven C M, Lelieveldt B P F, van der Geest R J,et al. Multistage Hybrid Active Appearance Model Matching: Segmentation of Left and Right Ventricles in Cardiac MR Images. IEEE Trans on Medical Imaging, 2001, 20(5): 415-423
[8]  Paragios N, Detiche R. Coupled Geodesic Active Regions for Image Segmentation: A Level Set Approach // Proc of the 6th European Conference on Computer Vision. Dublin, Ireland, 2000: 224-240
[9]  Cremers D, Schnrr C. Statistical Shape Knowledge in Variational Motion Segmentation. Image and Vision Computing, 2003, 21(1): 77-86
[10]  Leventon M E, Grimson W E L, Faugeras O. Statistical Shape Influence in Geodesic Active Contours // Proc of the IEEE Conference on Computer Vision and Pattern Recognition. Hilton Head Island, USA, 2000, Ⅰ: 316-323
[11]  Cootes T F, Taylor C J, Cooper D H, et al. Active Shape Models: Their Training and Application. Computer Vision and Image Understanding, 1995, 61(1): 38-59
[12]  Adalsteinsson D, Sethian J A, Affitiation A A. The Fast Construction of Extension Velocities in Level Set Methods. Journal of Computational Physics, 1999, 148(1): 2-22

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