Asymmetry Spectrum Imaging for Baby Diffusion Tractography

and the UNC/UMN Baby Connectome Project Consortium

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

5 Citations (Scopus)


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
EditorsAlbert C.S. Chung, James C. Gee, Paul A. Yushkevich, Siqi Bao
PublisherSpringer Verlag
Number of pages13
ISBN (Print)9783030203504
Publication statusPublished - 2019
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


Conference26th International Conference on Information Processing in Medical Imaging, IPMI 2019
CityHong Kong

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)


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