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Whole‐body T1 mapping improves the definition of adipose tissue: Consequences for automated image analysis
Author(s) -
Kullberg Joel,
Angelhed JanErik,
Lönn Lars,
Brandberg John,
Ahlström Håkan,
Frimmel Hans,
Johansson Lars
Publication year - 2006
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.20644
Subject(s) - computer science , segmentation , artificial intelligence , computer vision , histogram , automated method , whole body imaging , image (mathematics) , pattern recognition (psychology) , magnetic resonance imaging , medicine , radiology
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. J. Magn. Reson. Imaging 2006. © 2006 Wiley‐Liss, Inc.