Mosaic image segmentation with bias field correction

This paper presents an automatic method of correcting nonuniform RF coil response for the classification of body composition using MR imaging. By linear mosaic modelling, the smoothly but nonlinearly 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%.