Monté-Rubio, GC;
Falcón, C;
Pomarol-Clotet, E;
Ashburner, J;
(2018)
A comparison of various MRI feature types for characterizing whole brain anatomical differences using linear pattern recognition methods.
NeuroImage
, 178
pp. 753-768.
10.1016/j.neuroimage.2018.05.065.
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Abstract
There is a widespread interest in applying pattern recognition methods to anatomical neuroimaging data, but so far, there has been relatively little investigation into how best to derive image features in order to make the most accurate predictions. In this work, a Gaussian Process machine learning approach was used for predicting age, gender and body mass index (BMI) of subjects in the IXI dataset, as well as age, gender and diagnostic status using the ABIDE and COBRE datasets. MRI data were segmented and aligned using SPM12, and a variety of feature representations were derived from this preprocessing. We compared classification and regression accuracy using the different sorts of features, and with various degrees of spatial smoothing. Results suggested that feature sets that did not ignore the implicit background tissue class, tended to result in better overall performance, whereas some of the most commonly used feature sets performed relatively poorly.
Type: | Article |
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Title: | A comparison of various MRI feature types for characterizing whole brain anatomical differences using linear pattern recognition methods |
Location: | United States |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1016/j.neuroimage.2018.05.065 |
Publisher version: | https://doi.org/10.1016/j.neuroimage.2018.05.065 |
Language: | English |
Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
Keywords: | Diffeomorphism, Gaussian process, Model selection, Pattern recognition, Scalar momentum, Structural MRI, VBM |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience |
URI: | https://discovery.ucl.ac.uk/id/eprint/10050744 |
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