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Repeatability and accuracy of a novel, MRI-based, semi-automated analysis method for quantifying abdominal adipose tissue and thigh muscle volumes
Department of Radiology, University of California, San Diego, San Diego, CA, United States.
Department of Radiology, University of California, San Diego, San Diego, CA, United States.
Department of Radiology, University of California, San Diego, San Diego, CA, United States.
Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering. Advanced MR Analytics AB, Linköping, Sweden.ORCID iD: 0000-0002-9267-2191
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2016 (English)Conference paper, Poster (with or without abstract) (Other academic)
Abstract [en]

Current MRI methods to estimate body tissue compartment volumes rely on manual segmentation, which is laborious, expensive, not widely available outside specialized centers, and not standardized. To address these concerns, a novel, semi-automated image analysis method has been developed. Image acquisition takes about six minutes, and uses widely available MRI pulse sequences. We found that this method permits comprehensive body compartment analysis and provides high repeatability and accuracy. Current and future clinical and drug development studies may benefit from this methodology, as may clinical settings where monitoring change in these measures is desired.

Place, publisher, year, edition, pages
2016.
National Category
Radiology, Nuclear Medicine and Medical Imaging Medical Image Processing
Identifiers
URN: urn:nbn:se:liu:diva-128988OAI: oai:DiVA.org:liu-128988DiVA, id: diva2:933996
Conference
International Society for Magnetic Resonance in Medicine Annual Meeting & Exhibition, Singapore, May 7-13, 2016
Available from: 2016-06-07 Created: 2016-06-07 Last updated: 2019-06-14Bibliographically approved

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Borga, MagnusDahlqvist Leinhard, OlofRomu, Thobias

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Borga, MagnusDahlqvist Leinhard, OlofRomu, Thobias
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Center for Medical Image Science and Visualization (CMIV)Medical InformaticsFaculty of Science & EngineeringDivision of Radiological SciencesFaculty of Medicine and Health SciencesDepartment of Radiation Physics
Radiology, Nuclear Medicine and Medical ImagingMedical Image Processing

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CiteExportLink to record
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