Evaluations of diffusion tensor image registration based on fiber tractography. Issue 1 (December 2017)

• Record Type: Journal Article
• Authors: Wang, Yi; Shen, Yu; Liu, Dongyang; Li, Guoqin; Guo, Zhe; Fan, Yangyu; Niu, Yilong
• Is Part Of: Biomedical engineering online. Volume 16:Issue 1(2017)
• Page Start: 1
• Page End: 20
• Publication Date: 2017-12
• Subjects: DTI -- Registration algorithms -- Evaluation -- Tractography; Biomedical engineering -- Periodicals; 610.2805
• DOI: 10.1186/s12938-016-0299-2
• Languages: English
• ISSNs: 1475-925X

Abstract

Abstract Background Diffusion Tensor Magnetic Resonance Imaging (DT-MRI, also known as DTI) measures the diffusion properties of water molecules in tissues and to date is one of the main techniques that can effectively study the microstructures of the brain in vivo. Presently, evaluation of DTI registration techniques is still in an initial stage of development. Methods and results In this paper, six well-known open source DTI registration algorithms: Elastic, Rigid, Affine, DTI-TK, FSL and SyN were applied on 11 subjects from an open-access dataset, among which one was randomly chosen as the template. Eight different fiber bundles of 10 subjects and the template were obtained by drawing regions of interest (ROIs) around various structures using deterministic streamline tractography. The performances of the registration algorithms were evaluated by computing the distances and intersection angles between fiber tracts, as well as the fractional anisotropy (FA) profiles along the fiber tracts. Also, the mean squared error (MSE) and the residual MSE (RMSE) of fibers originating from the registered subjects and the template were calculated to assess the registration algorithm. Twenty-seven different fiber bundles of the 10 subjects and template were obtained by drawing ROIs around various structures using probabilistic tractography. The performances of registration algorithms on this second tractography method were evaluated by computing the spatial correlation similarity of the fibers between subjects as well as between each subject and the template. Conclusion All experimental results indicated that DTI-TK performed the best under the study conditions, and SyN ranked just behind it.