Centre de Vision Numérique (CVN)

Laboratory presentation

CVN is at the crossroads between mathematics and computer science. It focuses its research on computer vision and its numerous applications, machine learning, and the analysis of biomedical imagery. CVN is therefore active in varied research fields (from image reconstruction to autonomous vehicles, or even computer assisted surgery), making it an active partner with several industry leading corporations.

The 20 latest publications

Title Authors Publication date Source
Detection and severity quantification of pulmonary embolism with 3D CT data using an automated deep learning-based artificial solution Younes Belkouchi, Hugues Talbot 03/01/24 Diagnostic and interventional imaging
Deep learning for automatic bowel-obstruction identification on abdominal CT Maxence Gelard, Jean Christophe Pesquet, Emilie Chouzenoux 01/01/24 European Radiology
Prognostic value of automated assessment of interstitial lung disease on CT in systemic sclerosis Maria Vakalopoulou 01/01/24 Rheumatology
Joint Learning of Fully Connected Network Models in Lifting Based Image Coders Jean Christophe Pesquet 01/01/24 IEEE Transactions on Image Processing
MULTIPLICITY OF NEUTRALLY STABLE PERIODIC ORBITS WITH COEXISTENCE IN THE CHEMOSTAT SUBJECT TO PERIODIC REMOVAL RATE Thomas Guilmeau 01/01/24 SIAM Journal on Applied Mathematics
DeConDFFuse: Predicting drug–drug interaction using joint deep convolutional transform learning and decision forest fusion framework Emilie Chouzenoux 10/01/23 Expert Systems with Applications
Synergic prognostic value of 3D CT scan subcutaneous fat and muscle masses for immunotherapy-treated cancer Younes Belkouchi, Hugues Talbot 09/07/23 Journal for ImmunoTherapy of Cancer
Trastuzumab deruxtecan in metastatic breast cancer with variable HER2 expression: the phase 2 DAISY trial Vianney Baris, Pierre Laplante, P. L. Kannouche 08/01/23 Nature Medicine
Multiple Kernel Representation Learning on Networks Fragkiskos D. Malliaros 06/01/23 IEEE Transactions on Knowledge and Data Engineering
A computational two-photon fluorescence approach for revealing label-free the 3D image of viruses and bacteria Emilie Chouzenoux 05/01/23 Journal of Biophotonics
Synthetic MR image generation of macrotrabecular-massive hepatocellular carcinoma using generative adversarial networks Younes Belkouchi, Hugues Talbot 05/01/23 Diagnostic and interventional imaging
Graph Regularized Probabilistic Matrix Factorization for Drug-Drug Interactions Prediction Stuti Jain, Emilie Chouzenoux 05/01/23 IEEE Journal of Biomedical and Health Informatics
Better than RECIST and Faster than iRECIST: Defining the Immunotherapy Progression Decision Score to Better Manage Progressive Tumors on Immunotherapy Younes Belkouchi, Hugues Talbot 04/15/23 Clinical Cancer Research
A Local MM Subspace Method for Solving Constrained Variational Problems in Image Recovery Emilie Chouzenoux, Ségolène Martin, Jean Christophe Pesquet 04/01/23 Journal of Mathematical Imaging and Vision
Space-variant image reconstruction via Cauchy regularisation: Application to Optical Coherence Tomography Gabriele Scrivanti 04/01/23 Signal Processing
Block delayed Majorize-Minimize subspace algorithm for large scale image restoration Emilie Chouzenoux, Jean Baptiste Fest 04/01/23 Inverse Problems
Convergence analysis of block majorize-minimize subspace approach Emilie Chouzenoux, Jean Baptiste Fest 01/01/23 Optimization Letters
Generative adversarial networks (GAN)-based data augmentation of rare liver cancers: The SFR 2021 Artificial Intelligence Data Challenge Younes Belkouchi, Hugues Talbot 01/01/23 Diagnostic and interventional imaging
Artificial intelligence in musculoskeletal oncology imaging: A critical review of current applications Theodore Aouad 01/01/23 Diagnostic and interventional imaging
Proximal Splitting Adversarial Attack for Semantic Segmentation Jean Christophe Pesquet 01/01/23 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Number of publications of the laboratory by scientific field (2016-2021)

Every paper can be classified in one or more scientific fields. The figure below shows the lab's number of publications in each scientific field, according to the ASJC classification (Elsevier)