activity
20172022
most citedClinica: an open source software platform for reproducible clinical neuroscience studies

16 citations · 35 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV20221 cited

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…

q-bio.QM202116 cited

Clinica: an open source software platform for reproducible clinical neuroscience studies

Alexandre Routier, Ninon Burgos, Mauricio Díaz +21

We present Clinica (www.clinica.run), an open-source software platform designed to make clinical neuroscience studies easier and more reproducible. Clinica aims for researchers to…

eess.IV20192 cited

Visualization approach to assess the robustness of neural networks for medical image classification

Elina Thibeau Sutre, Olivier Colliot, Didier Dormont +1

The use of neural networks for diagnosis classification is becoming more and more prevalent in the medical imaging community. However, deep learning method outputs remain hard to e…

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…