Automatic Intra-Subject Registration-Based Segmentation of Abdominal Fat From Three-Dimensional Water–Fat MRI

Materials and Methods: Data were obtained from 11 subjects at two time points with intermediate repositioning, and from four subjects before and after a meal with repositioning. Imaging was performed on a 3 Tesla MRI, using the IDEAL chemical-shift water–fat pulse sequence. Adipose tissue (subcutaneous—SAT, visceral—VAT) and organs (liver, pancreas) were manually segmented twice for each scan by a single trained observer. Automated segmentations of each subject’s second scan were generated using a nonrigid volume registration algorithm for water–fat MRI images that used a b-spline basis for deformation and minimized image dissimilarity after the deformation. Manual and automated segmentations were compared using Dice coefficients and linear regression of SAT and VAT volumes, organ volumes, and hepatic and pancreatic fat fractions (HFF, PFF).