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

Article in a review
09/01/2019
Optimal Multivariate Gaussian Fitting with Applications to PSF Modeling in Two-Photon Microscopy Imaging
Emilie Chouzenoux, Tim Tsz-Kit Lau, Claire Lefort, Jean-Christophe Pesquet
Communication on a congress
08/26/2019
Communication on a congress
08/01/2019
Online MR image reconstruction for compressed sensing acquisition in T2* imaging
Loubna Gueddari, Emilie Chouzenoux, Alexandre Vignaud, Jean-Christophe Pesquet, Philippe Ciuciu
Communication on a congress
07/28/2019
Detecting urban changes with recurrent neural networks from multitemporal Sentinel-2 data
Maria Papadomanolaki, Sagar Verma, Maria Vakalopoulou, Siddharth Gupta, Konstantinos Karantzalos
Pre-submission / Working document
07/16/2019
Deep Unfolding of a Proximal Interior Point Method for Image Restoration
Carla Bertocchi, Emilie Chouzenoux, Marie-Caroline Corbineau, Jean-Christophe Pesquet, Marco Prato
Browse all laboratory submissions on HAL