title: Compensation of RF field and receiver coil induced inhomogeneity effects in abdominal MR images by a priori knowledge on the human adipose tissue distribution.
abstract: OBJECTIVE
  To reliably compensate bias field effects in abdominal areas to accurately quantify visceral adipose tissue using standard T1-weighted sequences on MR scanners with up to 3 Tesla (T) field strength.
  
  
  METHODS
  Compensation is achieved in two steps: The bias field is first estimated by picking and fitting sampling points from the subcutaneous adipose tissue, using active contours and a thin plate fitting spline. Then, additional sampling points from visceral adipose tissue compartments are detected by thresholding and the bias field estimation is refined. It was compared with an established method using a simulated abdominal image and real 3T data.
  
  
  RESULTS
  At low bias field amplitudes (40-50%), the simulation study showed a good reduction of the mean coefficients of variance (CV) for both approaches (>80%). At higher amplitudes, the CV reduction was significantly higher for our approach (83.6%), compared with LEMS (54.3%). In the real data study, our approach showed reliable reduction of the inhomogeneities, while the LEMS algorithm sometimes even amplified the inhomogeneities.
  
  
  CONCLUSIONS
  The proposed method enables accurate and reliable segmentation of abdominal adipose tissue using simple thresholding techniques, even in severely corrupted images slices, obtained when using high field strengths and/or phased-array coils.
authors.affiliation: Section on Experimental Radiology, 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: Fabian
authors.initials: F
authors.lastname: Springer
authors.forename: Bin
authors.initials: B
authors.lastname: Yang
authors.forename: Fritz
authors.initials: F
authors.lastname: Schick
mesh_terms: D000005:Abdomen / Q000033:anatomy & histology*; D000273:Adipose Tissue / Q000033:anatomy & histology* / Q000502:physiology; D050154:Adiposity / Q000502:physiology*; D016477:Artifacts; D001185:Artificial Intelligence; D004867:Equipment Design; D019544:Equipment Failure Analysis; D006801:Humans; D007089:Image Enhancement / Q000295:instrumentation / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000295:instrumentation* / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique / Q000295:instrumentation