Brain magnetic resonance image segmentation combined boundary and Markov random field
Jian Lin · Zhongguo yixue wulixue zazhi · 2015
Objective Based on the existing medical image segmentation methods for brain magnetic resonance image(MRI),taking the Alzheimer's disease(AD) data as the example, a method based on boundary and Markov random field(MRF),combined with Lie algebra and flow field theory, is proposed for image segmentation and registration. Methods The segmentation based on boundary was firstly used to remove skull and non-organization, and then, a MRF was used to segment the brain tissue, and finally combining Lie algebras with flow field theory, the standard registration was carried out for the images. The results were compared with the results of the most common statistical parametric mapping- voxel based morphometry. Results The comparative analysis of the AD patients' brain MRI data was more effective in segmenting brain tissue and locating brain activation areas. Conclusion The proposed method can significantly improve the segmentation effect.