Journal of Magnetic Resonance Imaging · 2006 · 36 citations · 28 references
ComputingBioengineeringBiomedical EngineeringBiomedical ImagingDiagnostic ImagingDiagnostic RadiologyAdipose TissueImage SegmentationImaging AnatomyMedical Image AnalysisMedical ImagingVolume SegmentationBody Composition MeasurementFat Mass DistributionHistogram AnalysisSegmentationTissue Volumetry Algorithms
PURPOSE: To determine whether a whole-body T1-mapping acquisition method improves the definition of adipose tissue (AT) and simplifies automated AT segmentation compared to an image-based method. MATERIALS AND METHODS: The study included 10 subjects. Two whole-body volumes were acquired from each subject using two different flip angles. Whole-body T1 maps were calculated from each pair of whole-body volumes. AT was automatically segmented from the T1 maps and from the original image slices. The results were evaluated using manually segmented slices as reference. RESULTS: The T1-mapping method segmented more of the reference AT than the image-based method, with mean values (standard deviations (SDs)) of 87.7(5.1)% and 81.1(5.2)%, respectively. Compared to the image-based method, the T1-mapping method gives better histogram separation of AT in whole-body volumes. The suggested method also provides an output with smaller in-slice AT intensity variations. CONCLUSION: The T1-mapping method improves the definition of AT. T1-based analysis is superior to analysis based on the original images, and allows fully automated and accurate whole-body AT segmentation.
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Skeletal muscle mass and distribution in 468 men and women aged 18–88 yr
Ian Janssen, Steven B. Heymsfield, ZiMian Wang et al. · Journal of Applied Physiology · 2000 · 3K citations
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Satish Kenchaiah, Jane C. Evans, Daniel Levy et al. · New England Journal of Medicine · 2002 · 3K citations
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