821 citations · 1.2k across the 15 of their papers we have counts for
5 papers · 1 filter
Parallel transport in shape analysis: a scalable numerical scheme
Maxime Louis, Alexandre Bône, Benjamin Charlier +1
The analysis of manifold-valued data requires efficient tools from Riemannian geometry to cope with the computational complexity at stake. This complexity arises from the always-in…
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…
Statistical learning of spatiotemporal patterns from longitudinal manifold-valued networks
Igor Koval, Jean-Baptiste Schiratti, Alexandre Routier +4
We introduce a mixed-effects model to learn spatiotempo-ral patterns on a network by considering longitudinal measures distributed on a fixed graph. The data come from repeated obs…
Yet Another ADNI Machine Learning Paper? Paving The Way Towards Fully-reproducible Research on Classification of Alzheimer's Disease
Jorge Samper-González, Ninon Burgos, Sabrina Fontanella +5
In recent years, the number of papers on Alzheimer's disease classification has increased dramatically, generating interesting methodological ideas on the use machine learning and…
White Matter Fiber Segmentation Using Functional Varifolds
Kuldeep Kumar, Pietro Gori, Benjamin Charlier +3
The extraction of fibers from dMRI data typically produces a large number of fibers, it is common to group fibers into bundles. To this end, many specialized distance measures, suc…