Literature DB >> 17354902

Anatomical modelling of the musculoskeletal system from MRI.

Benjamin Gilles1, Laurent Moccozet, Nadia Magnenat-Thalmann.   

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 = 1.5 mm, computation time = 15 min.

Entities:  

Mesh:

Year:  2006        PMID: 17354902     DOI: 10.1007/11866565_36

Source DB:  PubMed          Journal:  Med Image Comput Comput Assist Interv


  7 in total

1.  Sensitivity of hip tissues contact evaluation to the methods used for estimating the hip joint center of rotation.

Authors:  Ehsan Arbabi; Jerome Schmid; Ronan Boulic; Daniel Thalmann; Nadia Magnenat-Thalmann
Journal:  Med Biol Eng Comput       Date:  2012-02-29       Impact factor: 2.602

2.  Extreme leg motion analysis of professional ballet dancers via MRI segmentation of multiple leg postures.

Authors:  Jérôme Schmid; Jinman Kim; Nadia Magnenat-Thalmann
Journal:  Int J Comput Assist Radiol Surg       Date:  2010-05-13       Impact factor: 2.924

3.  Automated segmentation of psoas major muscle in X-ray CT images by use of a shape model: preliminary study.

Authors:  Naoki Kamiya; Xiangrong Zhou; Huayue Chen; Chisako Muramatsu; Takeshi Hara; Ryujiro Yokoyama; Masayuki Kanematsu; Hiroaki Hoshi; Hiroshi Fujita
Journal:  Radiol Phys Technol       Date:  2011-07-14

4.  A technique for semiautomatic segmentation of echogenic structures in 3D ultrasound, applied to infant hip dysplasia.

Authors:  Abhilash Rakkunedeth Hareendranathan; Myles Mabee; Kumaradevan Punithakumar; Michelle Noga; Jacob L Jaremko
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-06-20       Impact factor: 2.924

5.  Semiautomatic classification of acetabular shape from three-dimensional ultrasound for diagnosis of infant hip dysplasia using geometric features.

Authors:  Abhilash Rakkunedeth Hareendranathan; Dornoosh Zonoobi; Myles Mabee; Chad Diederichs; Kumaradevan Punithakumar; Michelle Noga; Jacob L Jaremko
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-12-26       Impact factor: 2.924

6.  Image guided medialization laryngoplasty.

Authors:  Ge Jin; Nakhoon Baek; James K Hahn; Steven Bielamowicz; Rajat Mittal; Raymond Walsh
Journal:  Comput Animat Virtual Worlds       Date:  2009-01-01       Impact factor: 1.020

7.  Three-Dimensional Magnetic Resonance Imaging Bone Models of the Hip Joint Using Deep Learning: Dynamic Simulation of Hip Impingement for Diagnosis of Intra- and Extra-articular Hip Impingement.

Authors:  Guodong Zeng; Celia Degonda; Adam Boschung; Florian Schmaranzer; Nicolas Gerber; Klaus A Siebenrock; Simon D Steppacher; Moritz Tannast; Till D Lerch
Journal:  Orthop J Sports Med       Date:  2021-11-24
  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.