CentraleSupélec

CentraleSupélec is an internationally-reputed Higher Education and Research Institution. Its excellence lies in its combination of fundamental and applied sciences for innovation with societal impact. For almost two centuries, CentraleSupélec's top engineers have been practicing their skills and knowledge for the development of corporate institutions and public organizations.

Digital Vision Center (CVN)

 

Research Topics

Associated with Inria Saclay, the Centre de Vision Numérique, created in 2011, is at the intersection between mathematics and computer science. It is in search of mathematical models and their IT solutions for automatic structuring, interpreting and understanding big (visual) data with a focus on machine learning, computer vision and discrete models in biomedical image analysis.

Computer Vision

Image reconstruction, border detection, segmentation with or without modeling, flow estimation and monitoring, image analysis, object recognition and large-scale 3D modeling based on a grammar

Machine Learning and Optimization

Self-learning, probabilistic graphical models, multiple instance learning, structured output regression, kernel methods, and multitask, online, or transfer learning, etc.

Biomedical Image Analysis (GALEN-Inria team)

Compressed reconstruction and detection, tumor detection, organ segmentation, image registration and deformable fusion, longitudinal modeling of organs, virtual anatomy, population studies and understanding of the brain, etc.

The Center of Visual Computing of CentraleSupelec & Inria, Saclay, Ile-de-France, organized a summer school in Biomedical Image Analysis: Modalities, Methodologies & Clinical Research at the Institut Henri Poincaré at the heart of Paris. This was an official event of the Medical Image Computing and Computer Assisted Intervention Society (MICCAI). Please find out all the lectures given for this special event.

Fields of Application

  • Complex industrial systems (automation, optical sorting, robotics, control systems, non-destructive testing)

  • Automotive Industry (assisted driving, pedestrian detection, cruise control, parking assistance)

  • Health (computer-aided diagnostics, multimodal sensors, data mining, biomarker imaging, computer-aided surgery) 

 

Key Figures

  • Instructor-researchers and researchers: 5
  • PhD students: 17
  • Technical and administrative staff: 3
  • Interns: 8
  • Patents: 1
  • Publications: 22

 

Academic Partners

Inria (France), École des Ponts ParisTech (France), Henri Mondor University Hospital (France), Georges Pompidou European Hospital (France), Pitié-Salpêtrière Hospital (France), Montpelier University Hospital (France), CentraleSupélec (France), Stanford University (USA), StonyBrook University (USA), University of Pennsylvania (USA), UCLA (USA), Technical University of Munich (Germany), University of Lugano (Switzerland), University of Oxford (UK), University College London (UK), University of Oulu (Finland), École Polytechnique de Montréal (Canada), International Institute of Information Technology, Hyderabad (India)

 

Business and Research Clusters

Digiteo, Medicen, Cap Digital

 

Industrial Partners

GE Healthcare, Siemens Medical Solutions, Intrasense, LLTech
 

Contact

 

Website: http://cvn.ecp.fr/

Director: Jean-Christophe PESQUET
Tel.: +33 (0)1 41 13 17 85
Fax: +33 (0)1 41 13 10 06

Email: Jean-Christophe.pesquet@centralesupelec.fr 

 

Latest submissions

Report
12/03/2018
Deep Unfolding of a Proximal Interior Point Method for Image Restoration
Carla Bertocchi, Emilie Chouzenoux, Marie-Caroline Corbineau, Jean-Christophe Pesquet, Marco Prato
Pre-submission / Working document
10/30/2018
Majorize-Minimize Adapted Metropolis-Hastings Algorithm
Yosra Marnissi, Emilie Chouzenoux, Amel Benazza-Benyahia, Jean-Christophe Pesquet
Report
10/22/2018
A review on graph optimization and algorithmic frameworks
Alessandro Benfenati, Emilie Chouzenoux, Laurent Duval, Jean-Christophe Pesquet, Aurélie Pirayre
Article in a review
10/10/2018
MATI: An efficient algorithm for influence maximization in social networks
Maria-Evgenia Rossiid, Bowen Shi, Nikolaos Tziortziotis, Fragkiskos Malliaros, Christos Giatsidis, Michalis Vazirgiannis
Communication on a congress
09/16/2018
Linear and Deformable Image Registration with 3D Convolutional Neural Networks
Stergios Christodoulidis, Mihir Sahasrabudhe, Maria Vakalopoulou, Guillaume Chassagnon, Marie-Pierre Revel, Stavroula Mougiakakou, Nikos Paragios
Browse all laboratory submissions on HAL