Local hybrid level-set method for MRA image segmentation

Hong, Qingqi; Li, Qingde; Tian, Jie

Abstract

In this paper, a local hybrid level-set method for medical image segmentation is presented. In proposed method, a locally fitted binary energy function is introduced into the hybrid level-set framework proposed by Zhang et al.. Compared with the globally specified threshold, the use of local binary fitting energy in the hybrid level-set method allows one to extract local image information more accurately, which is essential for enhancing the efficiency and effectiveness of the segmentation of inhomogeneous images. Experimental results on 3D medical images are presented to demonstrate the strengths of the proposed method.

Citation

Hong, Q., Li, Q., & Tian, J. (2010, June). Local hybrid level-set method for MRA image segmentation. Presented at 10th IEEE International Conference on Computer and Information Technology, CIT-2010, 7th IEEE International Conference on Embedded Software and Systems, ICESS-2010, ScalCom-2010

• Conference Name: 10th IEEE International Conference on Computer and Information Technology, CIT-2010, 7th IEEE International Conference on Embedded Software and Systems, ICESS-2010, ScalCom-2010
• Start Date: Jun 29, 2010
• End Date: Jul 1, 2010
• Acceptance Date: Dec 31, 2010
• Publication Date: Dec 31, 2010
• Journal: Proceedings - 10th IEEE International Conference on Computer and Information Technology, CIT-2010, 7th IEEE International Conference on Embedded Software and Systems, ICESS-2010, ScalCom-2010
• Pages: 1397 - 1402
• ISBN: 978-0-7695-4108-2
• DOI: https://doi.org/10.1109/CIT.2010.250
• Keywords: Level set; LBF energy; Intensity inhomogeneity; MRA image
• Public URL: https://hull-repository.worktribe.com/output/423868
• Publisher URL: https://ieeexplore.ieee.org/document/5577842/