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. 2018 Nov 2;5:120. doi: 10.3389/frobt.2018.00120

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Copyright © 2018 Cenek, Hu, York and Dahl.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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An illustration of the information flow through a data processing framework needed to analyse brain MRI scans to produce a diagnosis. The raw image sets are first pre-processed (tasks labeled p-), the structural features are extracted (tasks labeled f-), higher order features and measurements calculated from 2D and 3D composites (tasks labeled r- and f-r- respectively), and the final diagnosis model synthesizing the measurement vector of local, regional and global features. The back arrows show the flow of information while the gray arrows show the trace-back feedback needed for a transparent decision support tool used by a radiologist.