Literature DB >> 21376812

Avoiding asymmetry-induced bias in longitudinal image processing.

Martin Reuter1, Bruce Fischl2.   

Abstract

Longitudinal image processing procedures frequently transfer or pool information across time within subject, with the dual goals of reducing the variability and increasing the accuracy of the derived measures. In this note, we discuss common difficulties in longitudinal image processing, focusing on the introduction of bias, and describe the approaches we have taken to avoid them in the FreeSurfer longitudinal processing stream.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21376812      PMCID: PMC3260043          DOI: 10.1016/j.neuroimage.2011.02.076

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  15 in total

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  193 in total

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