Asymmetry Spectrum Imaging for Baby Diffusion Tractography

and theÂ UNC/UMNÂ BabyÂ ConnectomeÂ ProjectÂ Consortium

doi:10.1007/978-3-030-20351-1_24

Asymmetry Spectrum Imaging for Baby Diffusion Tractography

and theÂ UNC/UMNÂ BabyÂ ConnectomeÂ ProjectÂ Consortium

Department of Brain and Cognitive Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Citations (Scopus)

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	Albert C.S. Chung, James C. Gee, Paul A. Yushkevich, Siqi Bao
Publisher	Springer Verlag
Pages	319-331
Number of pages	13
ISBN (Print)	9783030203504
DOIs	https://doi.org/10.1007/978-3-030-20351-1_24
Publication status	Published - 2019
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/Territory	China
City	Hong Kong
Period	19/6/2 → 19/6/7

Bibliographical note

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.

Publisher Copyright:
© 2019, Springer Nature Switzerland AG.

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-030-20351-1_24

Cite this

and theÂ UNC/UMNÂ BabyÂ ConnectomeÂ ProjectÂ Consortium (2019). Asymmetry Spectrum Imaging for Baby Diffusion Tractography. In A. C. S. Chung, J. C. Gee, P. A. Yushkevich, & S. Bao (Eds.), Information Processing in Medical Imaging - 26th International Conference, IPMI 2019, Proceedings (pp. 319-331). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11492 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-20351-1_24

Asymmetry Spectrum Imaging for Baby Diffusion Tractography. / and theÂ UNC/UMNÂ BabyÂ ConnectomeÂ ProjectÂ Consortium.
Information Processing in Medical Imaging - 26th International Conference, IPMI 2019, Proceedings. ed. / Albert C.S. Chung; James C. Gee; Paul A. Yushkevich; Siqi Bao. 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

and theÂ UNC/UMNÂ BabyÂ ConnectomeÂ ProjectÂ Consortium 2019, Asymmetry Spectrum Imaging for Baby Diffusion Tractography. in ACS Chung, JC Gee, PA Yushkevich & S Bao (eds), Information Processing in Medical Imaging - 26th International Conference, IPMI 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11492 LNCS, Springer Verlag, pp. 319-331, 26th International Conference on Information Processing in Medical Imaging, IPMI 2019, Hong Kong, China, 19/6/2. https://doi.org/10.1007/978-3-030-20351-1_24

and theÂ UNC/UMNÂ BabyÂ ConnectomeÂ ProjectÂ Consortium. Asymmetry Spectrum Imaging for Baby Diffusion Tractography. In Chung ACS, Gee JC, Yushkevich PA, Bao S, editors, Information Processing in Medical Imaging - 26th International Conference, IPMI 2019, Proceedings. Springer Verlag. 2019. p. 319-331. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-20351-1_24

and theÂ UNC/UMNÂ BabyÂ ConnectomeÂ ProjectÂ Consortium. / Asymmetry Spectrum Imaging for Baby Diffusion Tractography. Information Processing in Medical Imaging - 26th International Conference, IPMI 2019, Proceedings. editor / Albert C.S. Chung ; James C. Gee ; Paul A. Yushkevich ; Siqi Bao. Springer Verlag, 2019. pp. 319-331 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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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.",

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note = "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. Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 26th International Conference on Information Processing in Medical Imaging, IPMI 2019 ; Conference date: 02-06-2019 Through 07-06-2019",

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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. Publisher Copyright: © 2019, Springer Nature Switzerland AG.

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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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Asymmetry Spectrum Imaging for Baby Diffusion Tractography

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