Pipeline-Invariant Representation Learning for Neuroimaging. (arXiv:2208.12909v1 [cs.LG])

Deep learning has been widely applied in neuroimaging, including to
predicting brain-phenotype relationships from magnetic resonance imaging (MRI)
volumes. MRI data usually requires extensive preprocessing before it is ready
for modeling, even via deep learning, in part due to its high dimensionality
and heterogeneity. A growing array of MRI preprocessing pipelines have been
developed each with its own strengths and limitations. Recent studies have
shown that pipeline-related variation may lead to different scientific
findings, even when using the identical data. …

arxiv learning neuroimaging pipeline representation representation learning