title: Segmentation of fat and muscle from MR images of the thigh by a possibilistic clustering algorithm.
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.
authors.affiliation: ERIM, Faculty of Medicine, BP 38, 63001 Clermont Ferrand Cédex, France. vincent.barra@u-clermont1.fr
authors.forename: Vincent
authors.initials: V
authors.lastname: Barra
authors.forename: Jean-Yves
authors.initials: JY
authors.lastname: Boire
mesh_terms: D000465:Algorithms; D005223:Fats / Q000032:analysis*; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D008875:Middle Aged; D009132:Muscles / Q000000981:diagnostic imaging*; D011859:Radiography; D015203:Reproducibility of Results; D013848:Thigh / Q000000981:diagnostic imaging*
chemical_list: D005223:Fats