2014
DOI: 10.1002/jmri.24726
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Automatic and quantitative assessment of regional muscle volume by multi‐atlas segmentation using whole‐body water–fat MRI

Abstract: The method accurately quantified the whole-body skeletal muscle volume and the volume of separate muscle groups independent of field strength and image resolution.

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Cited by 188 publications
(243 citation statements)
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“…The primary aim of the study was to measure test-retest reliability and not validate atlas based segmentation, which has been reported elsewhere (38) (39). Therefore we chose to manually segment only the VAT because we predicted that the proportionate measurement errors were going to be greatest in this compartment.…”
Section: Discussionmentioning
confidence: 99%
“…The primary aim of the study was to measure test-retest reliability and not validate atlas based segmentation, which has been reported elsewhere (38) (39). Therefore we chose to manually segment only the VAT because we predicted that the proportionate measurement errors were going to be greatest in this compartment.…”
Section: Discussionmentioning
confidence: 99%
“…Two imaging approaches are available for exploiting these differences, relaxation-dependent or short inversion-time recovery and chemical shift-dependent or Dixon-based fat suppression (82) . Karlsson et al recently reported development of a two-point Dixon sequence automated water-fat segmentation method for evaluating total body and regional skeletal muscle volume (83) . The authors showed excellent test-retest reliability (intraclass correlation coefficient 1·0, 95 % agreement level −0·32 to 0·2 litres) and agreement with hand-segmented images of the lower leg (correlation R values 0·94-0·96) in a followup study using a 3T wide-bore MRI scanner and integrated quadrature body coil (84) .…”
Section: Water-fat Imagingmentioning
confidence: 99%
“…Des essais de développement d'outils de segmentation automatique ont été entrepris, mais très peu d'entre eux sont parvenus à générer des résultats fiables, et aucun n'a encore permis d'analyser des images de muscles pathologiques présentant des infiltrations graisseuses. Très récemment, il a été rapporté qu'un logiciel de segmentation automatique s'appuyant sur un modèle générait des résul-tats très proches d'une segmentation manuelle (Karlsson et al 2015). Une approche naïve a éga-lement été proposée, où une estimation de la masse musculaire globale est calculée à partir de l'histogramme d'intensité de segments entiers de membres (Mattei et al 2006).…”
Section: Figureunclassified