Protecting regions of interest in medical images in a lossy packet network

We present two methods for protecting a region of interest (ROI) in a compressed medical image transmitted across a lossy packet network such as the Internet or a wireless channel. We begin with a high quality wavelet-based coder, the Set Partitioning in Hierarchical Trees (SPIHT) algorithm, which orders data progressively by coding the globally important information first. We then compress the ROI to a higher quality than the rest of the image by scaling the wavelet coefficients corresponding to the ROI. This approach moves ROI information earlier in the bit stream. Finally, we add more redundancy to the ROI than to the rest of the image by two techniques. With MD-SPIHT, we repeat wavelet coefficient trees corresponding to the ROI and code them to higher bit rates than the background trees. With ULP-FEC, we use forward error correction (FEC) in an unequal loss protection framework. We find that both methods increase the probability of receiving high quality ROI in the presence of packet loss.