22 citations · 27 across the 4 of their papers we have counts for
4 papers
Generalizable multi-task, multi-domain deep segmentation of sparse pediatric imaging datasets via multi-scale contrastive regularization and multi-joint anatomical priors
Arnaud Boutillon, Pierre-Henri Conze, Christelle Pons +2
Clinical diagnosis of the pediatric musculoskeletal system relies on the analysis of medical imaging examinations. In the medical image processing pipeline, semantic segmentation u…
Multi-Task, Multi-Domain Deep Segmentation with Shared Representations and Contrastive Regularization for Sparse Pediatric Datasets
Arnaud Boutillon, Pierre-Henri Conze, Christelle Pons +2
Automatic segmentation of magnetic resonance (MR) images is crucial for morphological evaluation of the pediatric musculoskeletal system in clinical practice. However, the accuracy…
Multi-Structure Deep Segmentation with Shape Priors and Latent Adversarial Regularization
Arnaud Boutillon, Bhushan Borotikar, Christelle Pons +2
Automatic segmentation of the musculoskeletal system in pediatric magnetic resonance (MR) images is a challenging but crucial task for morphological evaluation in clinical practice…
Healthy versus pathological learning transferability in shoulder muscle MRI segmentation using deep convolutional encoder-decoders
Pierre-Henri Conze, Sylvain Brochard, Valérie Burdin +2
Automatic segmentation of pathological shoulder muscles in patients with musculo-skeletal diseases is a challenging task due to the huge variability in muscle shape, size, location…