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Updated: Jun 14, 2026

Automated Joint Space Detection Improves Bone Segmentation Accuracy
Published on: November 28, 2025
Musculoskeletal MRI segmentation using multi-resolution simplex meshes with medial representations
Benjamin Gilles1, Nadia Magnenat-Thalmann
1MIRALab - University of Geneva, Battelle, Building A, 7 Route de Drize, CH-1227 Carouge, Switzerland. benjamin.gilles@miralab.unige.ch
Abstract:
The automatic segmentation of the musculoskeletal system from medical images is a particularly challenging task, due to its morphological complexity, its large variability in the population and its potentially large deformations. In this paper we propose a novel approach for musculoskeletal segmentation and registration based on simplex meshes. Such discrete models have already proven to be efficient and versatile for medical image segmentation. We extend the current framework by introducing a multi-resolution approach and a reversible medial representation, in order to reduce the complexity of geometric and non-penetration constraints computation. Our framework allows both inter and intra-patient registration (involving both rigid and elastic matching). We also show that the introduced representations facilitate morphological analysis. As a case study, we demonstrate that muscles, bones, ligaments and cartilages of the hip and the thigh can be registered at an interactive frame rate, in a time-efficient way (<30min), with a satisfactory accuracy ( approximately 1.5mm), and with a minimal amount of manual tasks.

