Research on algorithms based on Markov random models for diffusion tensor-magnetic resonance images / 南方医科大学学报
Journal of Southern Medical University
;
(12): 1562-1572, 2010.
Article
in Chinese
| WPRIM
| ID: wpr-336142
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.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Algorithms
/
Pattern Recognition, Automated
/
Image Interpretation, Computer-Assisted
/
Diffusion Magnetic Resonance Imaging
/
Methods
Type of study:
Controlled clinical trial
/
Health economic evaluation
Limits:
Humans
Language:
Chinese
Journal:
Journal of Southern Medical University
Year:
2010
Type:
Article
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