Reducing Activation-Related Bias in FMRI Registration

Luis Freire, Jeff Orchard, Mark Jenkinson, Jean François Mangin

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

3 Citations (Scopus)

Abstract

The presence of cerebral activation may bias motion correction estimates when registering FMRI time series. This problem may be solved through the use of specific registration methods, which incorporate or down-weight cerebral activation confounding signals during registration. In this paper, we evaluate the performance of different registration methods specifically designed to deal with the problem of activation presence. The methods studied here yielded better results than the traditional approaches based on least square metrics, almost totally eliminating the activation-related confounds.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsGuang-Zhong Yang, Tianzi Jiang
PublisherSpringer Verlag
Pages278-285
Number of pages8
ISBN (Print)3540228772, 9783540228776
DOIs
Publication statusPublished or Issued - 2004
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3150
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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