no code implementations • 27 Jul 2022 • Arnaud Boutillon, Pierre-Henri Conze, Christelle Pons, Valérie Burdin, Bhushan Borotikar
Clinical diagnosis of the pediatric musculoskeletal system relies on the analysis of medical imaging examinations.
no code implementations • 17 Feb 2022 • Arnaud Boutillon, Asma Salhi, Valérie Burdin, Bhushan Borotikar
This mapping is learned from a synthetic population generated by the standard SSM.
no code implementations • 21 May 2021 • Arnaud Boutillon, Pierre-Henri Conze, Christelle Pons, Valérie Burdin, Bhushan Borotikar
Automatic segmentation of magnetic resonance (MR) images is crucial for morphological evaluation of the pediatric musculoskeletal system in clinical practice.
no code implementations • 25 Jan 2021 • Arnaud Boutillon, Bhushan Borotikar, Christelle Pons, Valérie Burdin, Pierre-Henri Conze
Automatic segmentation of the musculoskeletal system in pediatric magnetic resonance (MR) images is a challenging but crucial task for morphological evaluation in clinical practice.
no code implementations • 15 Sep 2020 • Arnaud Boutillon, Bhushan Borotikar, Valérie Burdin, Pierre-Henri Conze
Morphological and diagnostic evaluation of pediatric musculoskeletal system is crucial in clinical practice.
no code implementations • 20 Oct 2019 • Arnaud Boutillon, Bhushan Borotikar, Valérie Burdin, Pierre-Henri Conze
This paper proposes an automatic method for scapula bone segmentation from Magnetic Resonance (MR) images using deep learning.