title: [Research on algorithms based on Markov random models for diffusion tensor-magnetic resonance images].
abstract: With the utilization of diffusion tensor information of image voxels, a novel MRF (Markov Random Field) segmentation algorithm was proposed for diffusion tensor MRI (DT-MRI) images benefitted from the introduction of Frobenius norm. The comparison of the segmentation effects between the proposed algorithm and K-means segmentation algorithm for DT-MRI image was made, which showed that the new algorithm could segment the DT-MRI images more accurately than the K-means algorithm. Moreover, with the same segmentation algorithm of MRF, better outcomes were achieved in DT-MRI than in conventional MRI (T2WI) image.
authors.affiliation: School of Biomedical Engineering, Southern Medical University. Guangzhou 510515, China.E-mail: cgirl1981@126.com.
authors.forename: Jie
authors.initials: J
authors.lastname: Peng
authors.forename: Qing-wen
authors.initials: QW
authors.lastname: Lü
authors.forename: Yan-qiu
authors.initials: YQ
authors.lastname: Feng
authors.forename: Yuan-yuan
authors.initials: YY
authors.lastname: Gao
authors.forename: Wu-fan
authors.initials: WF
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated