Multimodal neuroimaging computing: the workflows, methods, and platforms

Sidong Liu*, Weidong Cai, Siqi Liu, Fan Zhang, Michael Fulham, Dagan Feng, Sonia Pujol, Ron Kikinis

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

12 Citations (Scopus)
18 Downloads (Pure)

Abstract

The last two decades have witnessed the explosive growth in the development and use of noninvasive neuroimaging technologies that advance the research on human brain under normal and pathological conditions. Multimodal neuroimaging has become a major driver of current neuroimaging research due to the recognition of the clinical benefits of multimodal data, and the better access to hybrid devices. Multimodal neuroimaging computing is very challenging, and requires sophisticated computing to address the variations in spatiotemporal resolution and merge the biophysical/biochemical information. We review the current workflows and methods for multimodal neuroimaging computing, and also demonstrate how to conduct research using the established neuroimaging computing packages and platforms.

Original languageEnglish
Pages (from-to)181-195
Number of pages15
JournalBrain Informatics
Volume2
Issue number3
DOIs
Publication statusPublished - 1 Sep 2015
Externally publishedYes

Bibliographical note

Copyright the Author(s) 2015. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

  • Medical image computing
  • Multimodal
  • Neuroimaging

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