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2011 International Conference on Machine Learning and Cybernetics

DOI: 10.1109/icmlc.2011.6016989

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Vertebra segmentation of spine MRI with improved GVF snake based on shape knowledge

Proceedings article published in 2011 by Yong-Juan Zhao, Lin Shi, Jia-Chun Li, James F. Griffith, Anil T. Ahuja, Pheng-Ann Heng
This paper is available in a repository.
This paper is available in a repository.

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Abstract

In this paper, we apply GVF snake to vertebra segmentation and further improve it based on the knowledge of spine MRI, especially the shape knowledge. Owning to the contour of vertebra body being similar to a rectangle whose edges are concave to the center of the contour, we add a pressure force which moves the contour to the center as one of the external forces of snake, and then reset the weight coefficients of the external forces. The set of the weight coefficients can reach a target that the convergence rate is higher when the distance from the contour point to the center point is smaller. The experimental results show that the improved algorithm lowers the convergence rate and makes the segmentation result more accurate.