TY - GEN
T1 - Asymmetry Spectrum Imaging for Baby Diffusion Tractography
AU - and the UNC/UMN Baby Connectome Project Consortium
AU - Wu, Ye
AU - Lin, Weili
AU - Shen, Dinggang
AU - Yap, Pew Thian
N1 - Funding Information:
This work was supported in part by NIH grants (NS093842, EB022880, MH104324 and 1U01MH110274), a research grant from Nestec Ltd., and the efforts of the UNC/UMN Baby Connectome Project Consortium.
PY - 2019
Y1 - 2019
N2 - Fiber tractography in baby diffusion MRI is challenging due to the low and spatially-varying diffusion anisotropy, causing most tractography algorithms to yield streamlines that fall short of reaching the cortex. In this paper, we introduce a method called asymmetry spectrum imaging (ASI) to improve the estimation of white matter pathways in the baby brain by (i) incorporating an asymmetric fiber orientation model to resolve subvoxel fiber configurations such as fanning and bending, and (ii) explicitly modeling the range (or spectrum) of typical diffusion length scales in the developing brain. We validated ASI using in-vivo baby diffusion MRI data from the Baby Connectome Project (BCP), demonstrating that ASI can characterize complex subvoxel fiber configurations and accurately estimate the fiber orientation distribution function in spite of changes in diffusion patterns. This, in turn, results in significantly better diffusion tractography in the baby brain.
AB - Fiber tractography in baby diffusion MRI is challenging due to the low and spatially-varying diffusion anisotropy, causing most tractography algorithms to yield streamlines that fall short of reaching the cortex. In this paper, we introduce a method called asymmetry spectrum imaging (ASI) to improve the estimation of white matter pathways in the baby brain by (i) incorporating an asymmetric fiber orientation model to resolve subvoxel fiber configurations such as fanning and bending, and (ii) explicitly modeling the range (or spectrum) of typical diffusion length scales in the developing brain. We validated ASI using in-vivo baby diffusion MRI data from the Baby Connectome Project (BCP), demonstrating that ASI can characterize complex subvoxel fiber configurations and accurately estimate the fiber orientation distribution function in spite of changes in diffusion patterns. This, in turn, results in significantly better diffusion tractography in the baby brain.
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U2 - 10.1007/978-3-030-20351-1_24
DO - 10.1007/978-3-030-20351-1_24
M3 - Conference contribution
AN - SCOPUS:85066116826
SN - 9783030203504
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 319
EP - 331
BT - Information Processing in Medical Imaging - 26th International Conference, IPMI 2019, Proceedings
A2 - Chung, Albert C.S.
A2 - Gee, James C.
A2 - Yushkevich, Paul A.
A2 - Bao, Siqi
PB - Springer Verlag
T2 - 26th International Conference on Information Processing in Medical Imaging, IPMI 2019
Y2 - 2 June 2019 through 7 June 2019
ER -