activity
20182021
most citedAutomatic quality control of brain T1-weighted magnetic resonance images for a clinical data warehouse

3 citations · 3 across the 1 of their papers we have counts for

collaborators

5 papers

eess.IV20213 cited

Automatic quality control of brain T1-weighted magnetic resonance images for a clinical data warehouse

Simona Bottani, Ninon Burgos, Aurélien Maire +4

Many studies on machine learning (ML) for computer-aided diagnosis have so far been mostly restricted to high-quality research data. Clinical data warehouses, gathering routine exa…

cs.LG2020

Gaussian Graphical Model exploration and selection in high dimension low sample size setting

Thomas Lartigue, Simona Bottani, Stephanie Baron +3

Gaussian Graphical Models (GGM) are often used to describe the conditional correlations between the components of a random vector. In this article, we compare two families of GGM i…

cs.LG2019

Convolutional Neural Networks for Classification of Alzheimer's Disease: Overview and Reproducible Evaluation

Junhao Wen, Elina Thibeau-Sutre, Mauricio Diaz-Melo +7

Over 30 papers have proposed to use convolutional neural network (CNN) for AD classification from anatomical MRI. However, the classification performance is difficult to compare ac…

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…