title: Topography mapping of whole body adipose tissue using A fully automated and standardized procedure.
abstract: OBJECTIVE
  To obtain quantitative measures of human body fat compartments from whole body MR datasets for the risk estimation in subjects prone to metabolic diseases without the need of any user interaction or expert knowledge.
  
  
  METHODS
  Sets of axial T1-weighted spin-echo images of the whole body were acquired. The images were segmented using a modified fuzzy c-means algorithm. A separation of the body into anatomic regions along the body axis was performed to define regions with visceral adipose tissue present, and to standardize the results. In abdominal image slices, the adipose tissue compartments were divided into subcutaneous and visceral compartments using an extended snake algorithm. The slice-wise areas of different tissues were plotted along the slice position to obtain topographic fat tissue distributions.
  
  
  RESULTS
  Results from automatic segmentation were compared with manual segmentation. Relatively low mean deviations were obtained for the class of total tissue (4.48%) and visceral adipose tissue (3.26%). The deviation of total adipose tissue was slightly higher (8.71%).
  
  
  CONCLUSIONS
  The proposed algorithm enables the reliable and completely automatic creation of adipose tissue distribution profiles of the whole body from multislice MR datasets, reducing whole examination and analysis time to less than half an hour.
authors.affiliation: Department of Diagnostic and Interventional Radiology, University of Tübingen, Tübingen, Germany. christian.wuerslin@med.uni-tuebingen.de
authors.forename: Christian
authors.initials: C
authors.lastname: Würslin
authors.forename: Jürgen
authors.initials: J
authors.lastname: Machann
authors.forename: Hansjörg
authors.initials: H
authors.lastname: Rempp
authors.forename: Claus
authors.initials: C
authors.lastname: Claussen
authors.forename: Bin
authors.initials: B
authors.lastname: Yang
authors.forename: Fritz
authors.initials: F
authors.lastname: Schick
mesh_terms: D000273:Adipose Tissue / Q000033:anatomy & histology*; D000465:Algorithms; D001185:Artificial Intelligence; D050218:Body Fat Distribution / Q000379:methods* / Q000592:standards; D005858:Germany; D006801:Humans; D007089:Image Enhancement / Q000379:methods / Q000592:standards; D007090:Image Interpretation, Computer-Assisted / Q000379:methods* / Q000592:standards; D021621:Imaging, Three-Dimensional / Q000379:methods* / Q000592:standards; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000592:standards; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D051598:Whole Body Imaging / Q000379:methods* / Q000592:standards