22 citations · 82 across the 8 of their papers we have counts for
8 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…
Anatomically Parameterized Statistical Shape Model: Explaining Morphometry through Statistical Learning
Arnaud Boutillon, Asma Salhi, Valérie Burdin +1
Statistical shape models (SSMs) are a popular tool to conduct morphological analysis of anatomical structures which is a crucial step in clinical practices. However, shape represen…
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…
Multi-structure bone segmentation in pediatric MR images with combined regularization from shape priors and adversarial network
Arnaud Boutillon, Bhushan Borotikar, Valérie Burdin +1
Morphological and diagnostic evaluation of pediatric musculoskeletal system is crucial in clinical practice. However, most segmentation models do not perform well on scarce pediatr…
A fast and memory-efficient algorithm for smooth interpolation of polyrigid transformations: application to human joint tracking
K. Makki, B. Borotikar, M. Garetier +3
The log Euclidean polyrigid registration framework provides a way to smoothly estimate and interpolate poly-rigid/affine transformations for which the invertibility is guaranteed.…
Dynamic multi-object Gaussian process models: A framework for data-driven functional modelling of human joints
Jean-Rassaire Fouefack, Bhushan Borotikar, Tania S. Douglas +2
Statistical shape models (SSMs) are state-of-the-art medical image analysis tools for extracting and explaining features across a set of biological structures. However, a principle…
Combining Shape Priors with Conditional Adversarial Networks for Improved Scapula Segmentation in MR images
Arnaud Boutillon, Bhushan Borotikar, Valérie Burdin +1
This paper proposes an automatic method for scapula bone segmentation from Magnetic Resonance (MR) images using deep learning. The purpose of this work is to incorporate anatomical…