22 citations · 96 across the 11 of their papers we have counts for
11 papers
Note on the Existence of Minimizers for Variational Geometric Active Contours
El Hadji S. Diop, Valérie Burdin, V. B. Surya Prasath
We propose here a proof of existence of a minimizer of a segmentation functional based on a priori information on target shapes, and formulated with level sets. The existence of a…
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…
Dynamic multi feature-class Gaussian process models
Jean-Rassaire Fouefack, Bhushan Borotikar, Marcel Lüthi +3
In model-based medical image analysis, three features of interest are the shape of structures of interest, their relative pose, and image intensity profiles representative of some…
Bone Surface Reconstruction and Clinical Features Estimation from Sparse Landmarks and Statistical Shape Models: A feasibility study on the femur
Alireza Asvadi, Guillaume Dardenne, Jocelyne Troccaz +1
In this study, we investigated a method allowing the determination of the femur bone surface as well as its mechanical axis from some easy-to-identify bony landmarks. The reconstru…
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…
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…
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…