Functional magnetic resonance imaging (fMRI) combines high-resolution magnetic resonance imaging with neural activity and is widely used in medical image shooting and auxiliary diagnosis for its non-invasive, non-radiation, high spatial resolution and simultaneous imaging of function and morphology. This paper firstly introduces the medical image segmentation methods, and then presents two different level set segmentation methods: the edge-based Distance Regularized Level Set Evolution (DRLSE) Model and the region-based Region Scalable Fitting (RSF) Model. Finally, the simulation experiments are carried out on these two methods for comparative analysis. The results indicated that the proposed two kind of level set based methods performed high effectiveness in medical image segmentation.
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
Tel.: +1 703 830 6300
Fax: +1 703 830 2300 firstname.lastname@example.org
(Corporate matters and books only) IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042 email@example.com