416 citations · 475 across the 13 of their papers we have counts for
10 papers · 1 filter
Confidence intervals uncovered: Are we ready for real-world medical imaging AI?
Evangelia Christodoulou, Annika Reinke, Rola Houhou +19
Medical imaging is spearheading the AI transformation of healthcare. Performance reporting is key to determine which methods should be translated into clinical practice. Frequently…
Reproducibility in machine learning for medical imaging
Olivier Colliot, Elina Thibeau-Sutre, Ninon Burgos
Reproducibility is a cornerstone of science, as the replication of findings is the process through which they become knowledge. It is widely considered that many fields of science…
Interpretability of Machine Learning Methods Applied to Neuroimaging
Elina Thibeau-Sutre, Sasha Collin, Ninon Burgos +1
Deep learning methods have become very popular for the processing of natural images, and were then successfully adapted to the neuroimaging field. As these methods are non-transpar…
Learning Myelin Content in Multiple Sclerosis from Multimodal MRI through Adversarial Training
Wen Wei, Emilie Poirion, Benedetta Bodini +4
Multiple sclerosis (MS) is a demyelinating disease of the central nervous system (CNS). A reliable measure of the tissue myelin content is therefore essential for the understanding…
Learning distributions of shape trajectories from longitudinal datasets: a hierarchical model on a manifold of diffeomorphisms
Alexandre Bône, Olivier Colliot, Stanley Durrleman
We propose a method to learn a distribution of shape trajectories from longitudinal data, i.e. the collection of individual objects repeatedly observed at multiple time-points. The…
Prediction of the progression of subcortical brain structures in Alzheimer's disease from baseline
Alexandre Bône, Maxime Louis, Alexandre Routier +5
We propose a method to predict the subject-specific longitudinal progression of brain structures extracted from baseline MRI, and evaluate its performance on Alzheimer's disease da…