Asymmetry Spectrum Imaging for Baby Diffusion Tractography

and the UNC/UMN Baby Connectome Project Consortium

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (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 languageEnglish
Title of host publicationInformation Processing in Medical Imaging - 26th International Conference, IPMI 2019, Proceedings
EditorsSiqi Bao, Albert C.S. Chung, James C. Gee, Paul A. Yushkevich
PublisherSpringer Verlag
Pages319-331
Number of pages13
ISBN (Print)9783030203504
DOIs
Publication statusPublished - 2019 Jan 1
Event26th International Conference on Information Processing in Medical Imaging, IPMI 2019 - Hong Kong, China
Duration: 2019 Jun 22019 Jun 7

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11492 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference26th International Conference on Information Processing in Medical Imaging, IPMI 2019
CountryChina
CityHong Kong
Period19/6/219/6/7

Fingerprint

Asymmetry
Imaging
Imaging techniques
Fiber Orientation
Brain
Fiber
Fiber reinforced materials
Magnetic resonance imaging
Fibers
Configuration
Streamlines
Cortex
Length Scale
Distribution functions
Anisotropy
Pathway
Resolve
Distribution Function
Modeling
Estimate

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

and the UNC/UMN Baby Connectome Project Consortium (2019). Asymmetry Spectrum Imaging for Baby Diffusion Tractography. In S. Bao, A. C. S. Chung, J. C. Gee, & P. A. Yushkevich (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 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 proceedingConference contribution

and the UNC/UMN Baby Connectome Project Consortium 2019, Asymmetry Spectrum Imaging for Baby Diffusion Tractography. in S Bao, ACS Chung, JC Gee & PA Yushkevich (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 the UNC/UMN Baby Connectome Project Consortium. Asymmetry Spectrum Imaging for Baby Diffusion Tractography. In Bao S, Chung ACS, Gee JC, Yushkevich PA, 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)). https://doi.org/10.1007/978-3-030-20351-1_24
and the UNC/UMN Baby Connectome Project Consortium. / Asymmetry Spectrum Imaging for Baby Diffusion Tractography. Information Processing in Medical Imaging - 26th International Conference, IPMI 2019, Proceedings. editor / Siqi Bao ; Albert C.S. Chung ; James C. Gee ; Paul A. Yushkevich. Springer Verlag, 2019. pp. 319-331 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{56234ae962974691ba7c6555b5e0f5c7,
title = "Asymmetry Spectrum Imaging for Baby Diffusion Tractography",
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.",
author = "{and the{\^A} UNC/UMN{\^A} Baby{\^A} Connectome{\^A} Project{\^A} Consortium} and Ye Wu and Weili Lin and Dinggang Shen and Yap, {Pew Thian}",
year = "2019",
month = "1",
day = "1",
doi = "10.1007/978-3-030-20351-1_24",
language = "English",
isbn = "9783030203504",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "319--331",
editor = "Siqi Bao and Chung, {Albert C.S.} and Gee, {James C.} and Yushkevich, {Paul A.}",
booktitle = "Information Processing in Medical Imaging - 26th International Conference, IPMI 2019, Proceedings",

}

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 -