ROI approach to wavelet-based, hybrid compression of MR images

This paper presents a novel medical image compression technique for inhomogeneous spatial reconstruction of MR images of the brain. The images are decomposed to various scales using the wavelet transform and a new multiscale segmentation algorithm is used to select areas of high diagnostic importance (regions of interest-ROI). Those areas, corresponding to brain tissue, tumours, and other structures in the head are compressed for maximum reconstruction quality, while neighbouring areas are coarsely approximated. The background is rejected since it contains only noise and no useful data. The quality of the reconstructed image is very good, even at low bit-rates, since the bit allocation is performed after diagnosis and reflects the diagnostic importance of each region. No useful data is lost at the selected ROI.