TY - GEN
T1 - Non-rigid Registration of White Matter Tractography Using Coherent Point Drift Algorithm
AU - Wang, Wenjuan
AU - Liu, Jin
AU - Wang, Tengfei
AU - Hu, Zongtao
AU - Xia, Li
AU - Wang, Hongzhi
AU - Yang, Lizhuang
AU - Wong, Stephen T.C.
AU - Zhang, Xiaochu
AU - Li, Hai
N1 - Funding Information:
Acknowledgements. This work was supported by the National Key R&D Program of China (2017YFB1300204), Hefei Foreign Cooperation Project (ZR201801020002), Director’s Fund of Hefei Cancer Hospital of CAS (YZJJ2019C14, YZJJ2019A04), the Key R&D Program of Anhui Province (201904a07020104), the Natural Science Fund of Anhui Province (1708085MF141), as well as John S Dunn Research Foundation and TT and WF Chao Foundation (STCW).
Publisher Copyright:
© Springer Nature Switzerland AG 2019.
PY - 2019
Y1 - 2019
N2 - Axonal fibers in the white matter are in charge of bio-signal delivery and relate information between neurons within the nervous system and between neurons and peripheral target tissues. Tract-based analysis (TBA) can directly bridge white matter and its connected cerebral cortex to achieve a joint analysis of the brain’s structure and function. However, the accuracy of TBA is highly dependent on the quality of spatial registration of fiber bundles of different individuals to the standard space. In this paper, a non-rigid point registration, Coherent Point Drift (CPD), is applied for registration of fiber bundles. Both the fiber features and the registration accuracy are evaluated to determine the correspondence among fiber bundles. Experiment results on twelve real data showed higher registration accuracy of the proposed method on mean nearest neighbor distance and fractional anisotropy (FA) profiles than traditional registration methods, such as affine, elastic and Iterative Closest Point (ICP).
AB - Axonal fibers in the white matter are in charge of bio-signal delivery and relate information between neurons within the nervous system and between neurons and peripheral target tissues. Tract-based analysis (TBA) can directly bridge white matter and its connected cerebral cortex to achieve a joint analysis of the brain’s structure and function. However, the accuracy of TBA is highly dependent on the quality of spatial registration of fiber bundles of different individuals to the standard space. In this paper, a non-rigid point registration, Coherent Point Drift (CPD), is applied for registration of fiber bundles. Both the fiber features and the registration accuracy are evaluated to determine the correspondence among fiber bundles. Experiment results on twelve real data showed higher registration accuracy of the proposed method on mean nearest neighbor distance and fractional anisotropy (FA) profiles than traditional registration methods, such as affine, elastic and Iterative Closest Point (ICP).
KW - CPD
KW - DTI
KW - Registration
KW - Tract-based analysis
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U2 - 10.1007/978-3-030-33226-6_1
DO - 10.1007/978-3-030-33226-6_1
M3 - Conference contribution
AN - SCOPUS:85075562330
SN - 9783030332259
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 3
EP - 11
BT - Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy - 4th International Workshop, MBIA 2019, and 7th International Workshop, MFCA 2019, Held in Conjunction with MICCAI 2019, Proceedings
A2 - Zhu, Dajiang
A2 - Yan, Jingwen
A2 - Huang, Heng
A2 - Shen, Li
A2 - Thompson, Paul M.
A2 - Westin, Carl-Fredrik
A2 - Pennec, Xavier
A2 - Joshi, Sarang
A2 - Nielsen, Mads
A2 - Sommer, Stefan
A2 - Fletcher, Tom
A2 - Durrleman, Stanley
PB - Springer
T2 - 4th International Workshop on Multimodal Brain Image Analysis, MBAI 2019, and the 7th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer Assisted Intervention, MICCAI 2019
Y2 - 17 October 2019 through 17 October 2019
ER -