Title :
A Set-based Hybrid Approach (SHA) for MRI Segmentation
Author :
Liu, Jiang ; Leong, Tze-Yun ; Chee, Kin Ban ; Tan, Boon Pin ; Shuter, Borys ; Wang, Shih-Chang
Author_Institution :
Dept. of Comput. Sci., Nat. Univ. of Singapore
Abstract :
This paper describes a new hybrid approach set-based hybrid approach (SHA) for magnetic resonance (MR) image segmentation by integrating two existing techniques, region-grow and threshold level set. To evaluate the proposed approach in performing real world image segmentation task, instead of using well-taken MR-images, we use real-life images collected in a hospital. Comparison of the performance between the two individual techniques and the new hybrid technique demonstrates the effectiveness of the latter
Keywords :
biomedical MRI; image segmentation; medical image processing; set theory; magnetic resonance image segmentation; region growth; set-based hybrid approach; threshold level set; Biomedical imaging; Computer science; Differential equations; Image edge detection; Image segmentation; Level set; Magnetic resonance; Magnetic resonance imaging; Medical diagnostic imaging; Radiology;
Conference_Titel :
Control, Automation, Robotics and Vision, 2006. ICARCV '06. 9th International Conference on
Conference_Location :
Singapore
Print_ISBN :
1-4244-0341-3
Electronic_ISBN :
1-4214-042-1
DOI :
10.1109/ICARCV.2006.345358