title: Automatic MRI adipose tissue mapping using overlapping mosaics.
abstract: This paper presents an automatic method of correcting non-uniform RF coil response for the classification of body composition using MR imaging. By linear mosaic modelling, the smoothly but non-linearly varying bias field, which modulates tissue intensities within the image, was corrected. The overlapping between adjacent mosaics ensured consistent segmentation of body fat content and the effectiveness of the technique was validated by both phantom and in vivo experiments. Ten whole body composition data sets, each with 39 trans-axial slices, were acquired. Automatic segmentation results using the proposed technique were compared with those from manual delineations. The automatic segmentation method was found to be highly accurate and the mean percentage error between the two methods was less than 1.5%.
authors.affiliation: Royal Society/Wolfson Medical Image Computing Laboratory, Imperial College of Science, Technology and Medicine, 180 Queens Gate, SW7 2BZ, London, UK. gzy@doc.ic.ac.uk
authors.forename: G Z
authors.initials: GZ
authors.lastname: Yang
authors.forename: S
authors.initials: S
authors.lastname: Myerson
authors.forename: F
authors.initials: F
authors.lastname: Chabat
authors.forename: D J
authors.initials: DJ
authors.lastname: Pennell
authors.forename: D N
authors.initials: DN
authors.lastname: Firmin
mesh_terms: D000273:Adipose Tissue / Q000473:pathology*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015233:Models, Statistical; D009132:Muscles / Q000473:pathology; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted