Abstract
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.
| Original language | English |
|---|---|
| Title of host publication | Information Processing in Medical Imaging - 26th International Conference, IPMI 2019, Proceedings |
| Editors | Siqi Bao, Albert C.S. Chung, James C. Gee, Paul A. Yushkevich |
| Publisher | Springer Verlag |
| Pages | 319-331 |
| Number of pages | 13 |
| ISBN (Print) | 9783030203504 |
| DOIs | |
| Publication status | Published - 2019 Jan 1 |
| Event | 26th International Conference on Information Processing in Medical Imaging, IPMI 2019 - Hong Kong, China Duration: 2019 Jun 2 → 2019 Jun 7 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 11492 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Conference
| Conference | 26th International Conference on Information Processing in Medical Imaging, IPMI 2019 |
|---|---|
| Country | China |
| City | Hong Kong |
| Period | 19/6/2 → 19/6/7 |
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ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)
Cite this
Asymmetry Spectrum Imaging for Baby Diffusion Tractography. / and the UNC/UMN Baby Connectome Project Consortium.
Information Processing in Medical Imaging - 26th International Conference, IPMI 2019, Proceedings. ed. / Siqi Bao; Albert C.S. Chung; James C. Gee; Paul A. Yushkevich. Springer Verlag, 2019. p. 319-331 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11492 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
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
PY - 2019/1/1
Y1 - 2019/1/1
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.
UR - http://www.scopus.com/inward/record.url?scp=85066116826&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85066116826&partnerID=8YFLogxK
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 - Bao, Siqi
A2 - Chung, Albert C.S.
A2 - Gee, James C.
A2 - Yushkevich, Paul A.
PB - Springer Verlag
ER -