World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
33
Citations
11106
World Ranking
12375
National Ranking
312

Overview

Michel Dojat is affiliated with the French Institute for Research in Computer Science and Automation (INRIA) in France. Their research spans the fields of medicine and computer science, focusing particularly on medical imaging and artificial intelligence applications.

Their main areas of study include:

  • Medicine
  • Computer Science

Within these fields, Dojat's work concentrates on several subfields:

  • Radiology, Nuclear Medicine and Imaging
  • Artificial Intelligence
  • Neurology
  • Computer Vision and Pattern Recognition
  • Cognitive Neuroscience

Core research topics associated with their publications feature:

  • Medical Image Segmentation Techniques
  • Anomaly Detection Techniques and Applications
  • Radiomics and Machine Learning in Medical Imaging
  • Parkinson's Disease Mechanisms and Treatments
  • Advanced Neuroimaging Techniques and Applications
  • Neurological disorders and treatments
  • Cell Image Analysis Techniques

Michel Dojat has contributed to numerous scientific papers, some of the most recent being:

  • "Trustworthy clinical AI solutions: A unified review of uncertainty quantification in Deep Learning models for medical image analysis," 2024, published in Artificial Intelligence in Medicine
  • "Multiple sclerosis lesions segmentation from multiple experts: The MICCAI 2016 challenge dataset," 2021, published in NeuroImage
  • "ImUnity: A generalizable VAE-GAN solution for multicenter MR image harmonization," 2023, published in Medical Image Analysis
  • "Visual Dysfunction of the Superior Colliculus in De Novo Parkinsonian Patients," 2020, published in Annals of Neurology
  • "A Multicenter Preclinical MRI Study: Definition of Rat Brain Relaxometry Reference Maps," 2020, published in Frontiers in Neuroinformatics

Their collaborations include frequent co-authorship with:

  • Florence Forbes
  • Benjamin Lambert
  • Senan Doyle
  • Olivier Commowick
  • Frédéric Cervenansky

Michel Dojat has published in a variety of venues, including:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
  • Frontiers in Neuroinformatics

They have also contributed to book publications, including the following title published by Frontiers Media:

  • Automatic methods for multiple sclerosis new lesions detection and segmentation, 2023

Best Publications

  • The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

    Bjoern H. Menze;Andras Jakab;Stefan Bauer;Jayashree Kalpathy-Cramer

  • A multicenter randomized trial of computer-driven protocolized weaning from mechanical ventilation

    Francçois Lellouche;Jordi Mancebo;Philippe Jolliet;Jean Roeseler

  • Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure

    Olivier Commowick;Audrey Istace;Michaël Kain;Baptiste Laurent

  • fMRI retinotopic mapping--step by step.

    Jan Warnking;Michel Dojat;Anne Guérin-Dugué;Chantal Delon-Martin

  • Clinical Evaluation of a Computer-controlled Pressure Support Mode

    Michel Dojat;Alain Harf;Dominique Touchard;François Lemaire

  • Evaluation of a knowledge-based system providing ventilatory management and decision for extubation.

    Michel Dojat;Alain Harf;Dominique Touchard;Martine Laforest

  • Sequence of pattern onset responses in the human visual areas: an fMRI constrained VEP source analysis.

    S. Vanni;Jan Warnking;Michel Dojat;Chantal Delon-Martin

  • A knowledge-based system for assisted ventilation of patients in intensive care units.

    Michel Dojat;Laurence Brochard;François Lemaire;Alain Harf

  • Moving Illusory Contours Activate Primary Visual Cortex: an fMRI Study

    Mohamed Seghier;Michel Dojat;Chantal Delon-Martin;Christophe Rubin

  • NéoGanesh: a working system for the automated control of assisted ventilation in ICUs

    Michel Dojat;François Pachet;Zahia Guessoum;Dominique Touchard

  • A UMLS-based Knowledge Acquisition Tool for Rule-based Clinical Decision Support System Development

    Soumeya L. Achour;Michel Dojat;Claire Rieux;Philippe Bierling

  • Quantifying the watercolor effect: from stimulus properties to neural models

    Frédéric Devinck;Peggy Gerardin;Peggy Gerardin;Michel Dojat;Michel Dojat;Kenneth Knoblauch;Kenneth Knoblauch

  • The Neural Bases of Grapheme–Color Synesthesia Are Not Localized in Real Color-Sensitive Areas

    Jean-Michel Hupé;Cécile Bordier;Michel Dojat

  • Multimodal MRI segmentation of ischemic stroke lesions

    Y. Kabir;M. Dojat;B. Scherrer;C. Garbay

  • Computer-driven management of prolonged mechanical ventilation and weaning: a pilot study

    Lila Bouadma;François Lellouche;Belen Cabello;Solenne Taillé

  • Automated segmentation of human brain MR images using a multi-agent approach

    Nathalie Richard;Michel Dojat;Catherine Garbay

  • Towards an ontology for sharing medical images and regions of interest in neuroimaging

    Lynda Temal;Michel Dojat;Gilles Kassel;Bernard Gibaud

  • Distributed Local MRF Models for Tissue and Structure Brain Segmentation

    B. Scherrer;F. Forbes;C. Garbay;M. Dojat

  • Fast Joint Detection-Estimation of Evoked Brain Activity in Event-Related fMRI Using a Variational Approach

    L. Chaari;T. Vincent;F. Forbes;M. Dojat

  • Multiple sclerosis lesions segmentation from multiple experts: The MICCAI 2016 challenge dataset

    Olivier Commowick;Michaël Kain;Romain Casey;Roxana Ameli

  • A cooperative framework for segmentation of MRI brain scans.

    Laurence Germond;Michel Dojat;Christopher J. Taylor;Catherine Garbay

  • MSSEG-2 challenge proceedings: Multiple sclerosis new lesions segmentation challenge using a data management and processing infrastructure

    Olivier Commowick;Frédéric Cervenansky;François Cotton;Michel Dojat

Frequent Co-Authors

Kenneth Knoblauch
Kenneth Knoblauch Claude Bernard University Lyon 1
Christian Barillot
Christian Barillot Institut de Recherche en Informatique et Systèmes Aléatoires
Philippe Ciuciu
Philippe Ciuciu French Institute for Research in Computer Science and Automation - INRIA
Jean Bullier
Jean Bullier Grenoble Alpes University
Mélanie Pélégrini-Issac
Mélanie Pélégrini-Issac Sorbonne University
Olivier Commowick
Olivier Commowick French Institute for Research in Computer Science and Automation - INRIA
François Pachet
François Pachet Sorbonne University
Tristan Glatard
Tristan Glatard Concordia University
Johan Montagnat
Johan Montagnat Centre national de la recherche scientifique, CNRS
Grégoire Malandain
Grégoire Malandain French Institute for Research in Computer Science and Automation - INRIA

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring a computer science degree opens up a variety of online learning and career options. If you’re looking for the fastest route to a technology job, consider enrolling in a fast track computer science degree. This pathway is ideal for motivated students eager to enter the workforce quickly.

Computer science knowledge can also lead to roles at the intersection of technology and the environment. Curious how your technical skills might transfer? Discover what can you do with an environmental science major to explore careers that address today’s environmental challenges.

For those interested in engineering alongside computer science, affordable online degrees offer great flexibility. You might look into programs like an environmental engineering online degree or an online degree in mechanical engineering. Both fields increasingly rely on computer science expertise for design, simulation, and data analysis.

By considering these related online degrees and career pathways, you can better align your studies with your professional goals in technology, engineering, or environmental science.

Best Scientists Citing Michel Dojat

Trending Scientists

Recently Published Articles