activity
20162026
most citedMultidimensional classification of hippocampal shape features discriminates Alzheimer's disease and mild cognitive impairment from normal aging

416 citations · 494 across the 21 of their papers we have counts for

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Showing 2018Show all

6 papers · 1 filter

q-bio.NC2018

Disrupted core-periphery structure of multimodal brain networks in Alzheimer's Disease

Jeremy Guillon, Mario Chavez, Federico Battiston +7

In Alzheimer's disease (AD), the progressive atrophy leads to aberrant network reconfigurations both at structural and functional levels. In such network reorganization, the core a…

q-bio.QM2018

Reproducible evaluation of diffusion MRI features for automatic classification of patients with Alzheimers disease

Junhao Wen, Jorge Samper-Gonzalez, Simona Bottani +8

Diffusion MRI is the modality of choice to study alterations of white matter. In past years, various works have used diffusion MRI for automatic classification of AD. However, clas…

cs.LG2018

Reproducible evaluation of classification methods in Alzheimer's disease: framework and application to MRI and PET data

Jorge Samper-González, Ninon Burgos, Simona Bottani +13

A large number of papers have introduced novel machine learning and feature extraction methods for automatic classification of AD. However, they are difficult to reproduce because…

q-bio.QM2018

Converting Alzheimer s disease map into a heavyweight ontology: a formal network to integrate data

Vincent Henry, Ivan Moszer, Olivier Dameron +3

Alzheimer s disease (AD) pathophysiology is still imperfectly understood and current paradigms have not led to curative outcome. Omics technologies offer great promises for improvi…

cs.CV2018

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…

cs.CV2018

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…