Literature DB >> 12074845

Segmentation of fat and muscle from MR images of the thigh by a possibilistic clustering algorithm.

Vincent Barra1, Jean-Yves Boire.   

Abstract

Physical training is proved to induce changes in physical capacity and body composition. We propose in this article a fast, unsupervised and fully three-dimensional automatic method to extract muscle and fat volumes from magnetic resonance images of thighs in order to assess these changes. The technique relies on the use of a fuzzy clustering algorithm and post-processings to accurately process the body composition of thighs. Results are compared on 11 healthy voluntary elderly people with those provided on the same data by a validated method already published, and its reliability is assessed on repeated measures on three subjects. The two methods statistically agree when computing muscle and fat volumes, and clinical implications of this fully automatic method are important for medicine, physical conditioning, weight-loss programs and predictions of optimal body weight.

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Year:  2002        PMID: 12074845     DOI: 10.1016/s0169-2607(01)00172-9

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  12 in total

1.  An investigation into the use of MR imaging to determine the functional cross sectional area of lumbar paraspinal muscles.

Authors:  Craig A Ranson; Angus F Burnett; Robert Kerslake; Mark E Batt; Peter B O'Sullivan
Journal:  Eur Spine J       Date:  2005-05-14       Impact factor: 3.134

2.  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

3.  Segmentation of fascias, fat and muscle from magnetic resonance images in humans: the DISPIMAG software.

Authors:  J P Mattei; Y Le Fur; N Cuge; S Guis; P J Cozzone; D Bendahan
Journal:  MAGMA       Date:  2006-09-27       Impact factor: 2.310

4.  Automated quantification of muscle and fat in the thigh from water-, fat-, and nonsuppressed MR images.

Authors:  Sokratis Makrogiannis; Suraj Serai; Kenneth W Fishbein; Catherine Schreiber; Luigi Ferrucci; Richard G Spencer
Journal:  J Magn Reson Imaging       Date:  2011-12-14       Impact factor: 4.813

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

6.  Automated segmentation and shape characterization of volumetric data.

Authors:  Vitaly L Galinsky; Lawrence R Frank
Journal:  Neuroimage       Date:  2014-02-09       Impact factor: 6.556

7.  Physical function, muscle strength and muscle mass in children on peritoneal dialysis.

Authors:  Gamze Alayli; Ozan Ozkaya; Kenan Bek; Altan Calmaşur; Bariş Diren; Yüksel Bek; Ferhan Cantürk
Journal:  Pediatr Nephrol       Date:  2008-01-16       Impact factor: 3.714

8.  Novel stochastic framework for automatic segmentation of human thigh MRI volumes and its applications in spinal cord injured individuals.

Authors:  Samineh Mesbah; Ahmed M Shalaby; Sean Stills; Ahmed M Soliman; Andrea Willhite; Susan J Harkema; Enrico Rejc; Ayman S El-Baz
Journal:  PLoS One       Date:  2019-05-09       Impact factor: 3.240

9.  Magnetic resonance imaging of the erector spinae muscles in Duchenne muscular dystrophy: implication for scoliotic deformities.

Authors:  Gnahoua Zoabli; Pierre A Mathieu; Carl-Eric Aubin
Journal:  Scoliosis       Date:  2008-12-29

10.  Repeatability of Dixon magnetic resonance imaging and magnetic resonance spectroscopy for quantitative muscle fat assessments in the thigh.

Authors:  Alexandra Grimm; Heiko Meyer; Marcel D Nickel; Mathias Nittka; Esther Raithel; Oliver Chaudry; Andreas Friedberger; Michael Uder; Wolfgang Kemmler; Klaus Engelke; Harald H Quick
Journal:  J Cachexia Sarcopenia Muscle       Date:  2018-09-16       Impact factor: 12.910

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