MEDICAL IMAGE COMPRESSION WITH LOSSLESS REGIONS OF INTEREST

Many classes of images contain some spatial regions which are more imp ortant than other regions. Compression methods which are capable of de livering higher reconstruction quality for the important parts are att ractive in this situation. For medical images, only a small portion of the image might be diagnostically useful, but the cost of a wrong int erpretation is high. Algorithms which deliver lossless compression wit hin the regions of interest, and lossy compression elsewhere in the im age, might be the key to providing efficient and accurate image coding to the medical community. We present and compare several new algorith ms for lossless region-of-interest (ROI) compression. One is based on lossless coding with the S-transform, and two are based on lossy wavel et zerotree coding together with either pixel-domain or transform-doma in coding of the regional residual. We survey previous methods for reg ion-based coding of medical images.