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An a contrario approach for the detection of patient-specific brain perfusion abnormalities with arterial spin labelling
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Maumet, Camille, Maurel, Pierre, Ferré, Jean-Christophe and Barillot, Christian (2016) An a contrario approach for the detection of patient-specific brain perfusion abnormalities with arterial spin labelling. NeuroImage, 134 . pp. 424-433. doi:10.1016/j.neuroimage.2016.03.054 ISSN 1053-8119.
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Official URL: http://dx.doi.org/10.1016/j.neuroimage.2016.03.054
Abstract
In this paper, we introduce a new locally multivariate procedure to quantitatively extract voxel-wise patterns of abnormal perfusion in individual patients. This a contrario approach uses a multivariate metric from the computer vision community that is suitable to detect abnormalities even in the presence of closeby hypo- and hyper-perfusions. This method takes into account local information without applying Gaussian smoothing to the data. Furthermore, to improve on the standard a contrario approach, which assumes white noise, we introduce an updated a contrario approach that takes into account the spatial coherency of the noise in the probability estimation.
Validation is undertaken on a dataset of 25 patients diagnosed with brain tumours and 61 healthy volunteers. We show how the a contrario approach outperforms the massively univariate general linear model usually employed for this type of analysis.
Item Type: | Journal Article | ||||||||
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | ||||||||
Journal or Publication Title: | NeuroImage | ||||||||
Publisher: | Elsevier | ||||||||
ISSN: | 1053-8119 | ||||||||
Official Date: | 1 July 2016 | ||||||||
Dates: |
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Volume: | 134 | ||||||||
Page Range: | pp. 424-433 | ||||||||
DOI: | 10.1016/j.neuroimage.2016.03.054 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Restricted or Subscription Access |
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