{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T11:15:01Z","timestamp":1780658101733,"version":"3.54.1"},"reference-count":40,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2014,1,15]],"date-time":"2014-01-15T00:00:00Z","timestamp":1389744000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Magnetic Resonance Imaging"],"published-print":{"date-parts":[[2015,1]]},"abstract":"<jats:sec><jats:title>Purpose<\/jats:title><jats:p>To validate a fully automated adipose segmentation method with magnetic resonance imaging (MRI) fat fraction abdominal imaging. We hypothesized that this method is suitable for segmentation of subcutaneous adipose tissue (SAT) and intra\u2010abdominal adipose tissue (IAAT) in a wide population range, easy to use, works with a variety of hardware setups, and is highly repeatable.<\/jats:p><\/jats:sec><jats:sec><jats:title>Materials and Methods<\/jats:title><jats:p>Analysis was performed comparing precision and analysis time of manual and automated segmentation of single\u2010slice imaging, and volumetric imaging (78\u201388 slices). Volumetric and single\u2010slice data were acquired in a variety of cohorts (body mass index [BMI] 15.6\u201341.76) including healthy adult volunteers, adolescent volunteers, and subjects with nonalcoholic fatty liver disease and lipodystrophies. A subset of healthy volunteers was analyzed for repeatability in the measurements.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The fully automated segmentation was found to have excellent agreement with manual segmentation with no substantial bias across all study cohorts. Repeatability tests showed a mean coefficient of variation of 1.2\u2009\u00b1\u20090.6% for SAT, and 2.7\u2009\u00b1\u20092.2% for IAAT. Analysis with automated segmentation was rapid, requiring 2 seconds per slice compared with 8 minutes per slice with manual segmentation.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>We demonstrate the ability to accurately and rapidly segment regional adipose tissue using fat fraction maps across a wide population range, with varying hardware setups and acquisition methods. <jats:bold>J. Magn. Reson. Imaging 2015;41:233\u2013241.<\/jats:bold> \u00a9 <jats:bold>2014 Wiley Periodicals, Inc<\/jats:bold>.<\/jats:p><\/jats:sec>","DOI":"10.1002\/jmri.24526","type":"journal-article","created":{"date-parts":[[2014,1,16]],"date-time":"2014-01-16T05:08:41Z","timestamp":1389848921000},"page":"233-241","source":"Crossref","is-referenced-by-count":45,"title":["Validation of volumetric and single\u2010slice MRI adipose analysis using a novel fully automated segmentation method"],"prefix":"10.1002","volume":"41","author":[{"given":"Bryan T.","family":"Addeman","sequence":"first","affiliation":[{"name":"Department of Medical Biophysics University of Western Ontario London Ontario Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shelby","family":"Kutty","sequence":"additional","affiliation":[{"name":"University of Nebraska Medical Center Omaha Nebraska USA"},{"name":"Children's Hospital &amp; Medical Center Omaha Nebraska 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