Literature DB >> 21855242

Automatic quantification of muscle volumes in magnetic resonance imaging scans of the lower extremities.

Gerd Brunner1, Vijay Nambi, Eric Yang, Anirudh Kumar, Salim S Virani, Panagiotis Kougias, Dipan Shah, Alan Lumsden, Christie M Ballantyne, Joel D Morrisett.   

Abstract

Muscle volume measurements are essential for an array of diseases ranging from peripheral arterial disease, muscular dystrophies, neurological conditions to sport injuries and aging. In the clinical setting, muscle volume is not routinely measured due to the lack of standardized ways for its repeatable quantification. In this paper, we present magnetic resonance muscle quantification (MRMQ), a method for the automatic quantification of thigh muscle volume in magnetic resonance imaging (MRI) scans. MRMQ integrates a thigh segmentation and nonuniform image gradient correction step, followed by feature extraction and classification. The classification step leverages prior probabilities, introducing prior knowledge to a maximum a posteriori classifier. MRMQ was validated on 344 slices taken from 60 MRI scans. Experiments for the fully automatic detection of muscle volume in MRI scans demonstrated an averaged accuracy, sensitivity and specificity for leave-one-out cross-validation of 88.3%, 93.6% and 87.2%, respectively.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21855242     DOI: 10.1016/j.mri.2011.02.033

Source DB:  PubMed          Journal:  Magn Reson Imaging        ISSN: 0730-725X            Impact factor:   2.546


  12 in total

Review 1.  Quantitative proton MR techniques for measuring fat.

Authors:  H H Hu; H E Kan
Journal:  NMR Biomed       Date:  2013-10-03       Impact factor: 4.044

2.  Calf muscle perfusion as measured with magnetic resonance imaging to assess peripheral arterial disease.

Authors:  Gerd Brunner; Jean Bismuth; Vijay Nambi; Christie M Ballantyne; Addison A Taylor; Alan B Lumsden; Joel D Morrisett; Dipan J Shah
Journal:  Med Biol Eng Comput       Date:  2016-02-23       Impact factor: 2.602

3.  Quantifying Abdominal Adipose Tissue and Thigh Muscle Volume and Hepatic Proton Density Fat Fraction: Repeatability and Accuracy of an MR Imaging-based, Semiautomated Analysis Method.

Authors:  Michael S Middleton; William Haufe; Jonathan Hooker; Magnus Borga; Olof Dahlqvist Leinhard; Thobias Romu; Patrik Tunón; Gavin Hamilton; Tanya Wolfson; Anthony Gamst; Rohit Loomba; Claude B Sirlin
Journal:  Radiology       Date:  2017-03-09       Impact factor: 11.105

4.  Test-retest reliability of automated whole body and compartmental muscle volume measurements on a wide bore 3T MR system.

Authors:  Marianna S Thomas; David Newman; Olof Dahlqvist Leinhard; Bahman Kasmai; Richard Greenwood; Paul N Malcolm; Anette Karlsson; Johannes Rosander; Magnus Borga; Andoni P Toms
Journal:  Eur Radiol       Date:  2014-05-29       Impact factor: 5.315

5.  Automatic quadriceps and patellae segmentation of MRI with cascaded U2 -Net and SASSNet deep learning model.

Authors:  Ruida Cheng; Marion Crouzier; François Hug; Kylie Tucker; Paul Juneau; Evan McCreedy; William Gandler; Matthew J McAuliffe; Frances T Sheehan
Journal:  Med Phys       Date:  2021-11-22       Impact factor: 4.506

Review 6.  Segmentation and quantification of adipose tissue by magnetic resonance imaging.

Authors:  Houchun Harry Hu; Jun Chen; Wei Shen
Journal:  MAGMA       Date:  2015-09-04       Impact factor: 2.310

7.  Thigh muscle segmentation of chemical shift encoding-based water-fat magnetic resonance images: The reference database MyoSegmenTUM.

Authors:  Sarah Schlaeger; Friedemann Freitag; Elisabeth Klupp; Michael Dieckmeyer; Dominik Weidlich; Stephanie Inhuber; Marcus Deschauer; Benedikt Schoser; Sarah Bublitz; Federica Montagnese; Claus Zimmer; Ernst J Rummeny; Dimitrios C Karampinos; Jan S Kirschke; Thomas Baum
Journal:  PLoS One       Date:  2018-06-07       Impact factor: 3.240

8.  Relation of Magnetic Resonance Imaging Based Arterial Signal Enhancement to Markers of Peripheral Artery Disease.

Authors:  Olga A Gimnich; Jonathan Holbrook; Tatiana Belousova; Christina M Short; Addison A Taylor; Vijay Nambi; Joel D Morrisett; Christie M Ballantyne; Jean Bismuth; Dipan J Shah; Gerd Brunner
Journal:  Am J Cardiol       Date:  2020-11-02       Impact factor: 2.778

9.  Feasibility of MR-Based Body Composition Analysis in Large Scale Population Studies.

Authors:  Janne West; Olof Dahlqvist Leinhard; Thobias Romu; Rory Collins; Steve Garratt; Jimmy D Bell; Magnus Borga; Louise Thomas
Journal:  PLoS One       Date:  2016-09-23       Impact factor: 3.240

10.  Precision of MRI-based body composition measurements of postmenopausal women.

Authors:  Janne West; Thobias Romu; Sofia Thorell; Hanna Lindblom; Emilia Berin; Anna-Clara Spetz Holm; Lotta Lindh Åstrand; Anette Karlsson; Magnus Borga; Mats Hammar; Olof Dahlqvist Leinhard
Journal:  PLoS One       Date:  2018-02-07       Impact factor: 3.240

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