Fiber tracking of brain white matter based on graph theory

被引:0
作者
Lu, Meng [1 ]
机构
[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang, Liaoning, Peoples R China
基金
中国国家自然科学基金;
关键词
Brain white matter; graph theory; QBI; tractography; Bayesian model; DIFFUSION-WEIGHTED MRI; TENSOR; TRACTOGRAPHY;
D O I
10.3233/THC-150921
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Brain white matter tractography is reconstructed via diffusion-weighted magnetic resonance images. Due to the complex structure of brain white matter fiber bundles, fiber crossing and fiber branching are abundant in human brain. And regular methods with diffusion tensor imaging (DTI) can't accurately handle this problem. the biggest problems of the brain tractography. Therefore, this paper presented a novel brain white matter tractography method based on graph theory, so the fiber tracking between two voxels is transformed into locating the shortest path in a graph. Besides, the presented method uses Q-ball imaging (QBI) as the source data instead of DTI, because QBI can provide accurate information about multiple fiber crossing and branching in one voxel using orientation distribution function (ODF). Experiments showed that the presented method can accurately handle the problem of brain white matter fiber crossing and branching, and reconstruct brain tractograhpy both in phantom data and real brain data.
引用
收藏
页码:S3 / S8
页数:6
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