Medical Image Compression with Lossless Regions of Interest

Many classes of images contain some spatial regions which are more important than other regions. Compression methods which are capable of delivering higher reconstruction quality for the important parts are attractive in this situation. For medical images, only a small portion of the image might be diagnostically useful, but the cost of a wrong interpretation is high. Algorithms which delive lossless compression within the regions of interest, and lossy compression elsewhere in the image, might be the key to providing efficient and accurate image coding to the medical community. We present and compare several new algorithms for lossless region-of-interst (ROI) compression. One is based on lossless coding with the S_transform, and two are based on lossy wavelet zerotree coding together with either pixel-domain or transform-domain coding of the regional residue. We survey previous methods for region-based coding of medical images