Anatomical Modelling of the Musculoskeletal System from MRI

TLDR

The study introduces a novel automatic registration and segmentation method for the musculoskeletal system from clinical MRI using discrete deformable simplex mesh models. It achieves efficient, real‑time segmentation by combining multi‑resolution forces, hierarchical collision handling, large implicit time steps, radial forces, topological constraints, and a medial‑axis constrained shape approximation. Validation on four hip‑joint and thigh datasets (20 muscles, 4 bones) shows an average error of 1.5 mm and a computation time of 15 min.

Abstract

This paper presents a novel approach for multi-organ (musculoskeletal system) automatic registration and segmentation from clinical MRI datasets, based on discrete deformable models (simplex meshes). We reduce the computational complexity using multi-resolution forces, multi-resolution hierarchical collision handling and large simulation time steps (implicit integration scheme), allowing real-time user control and cost-efficient segmentation. Radial forces and topological constraints (attachments) are applied to regularize the segmentation process. Based on a medial axis constrained approximation, we efficiently characterize shapes and deformations. We validate our methods for the hip joint and the thigh (20 muscles, 4 bones) on 4 datasets: average error=1.5mm, computation time=15min.