Medical image compression using region-of-interest vector quantization

In this paper, we propose a region based image compression approach for medical applications. We use a Vector Quantization scheme, combined with Regions-Of-Interest. The image to be compressed is first segmented into regions and a separate codebook is used for each specified region. Codeword size and number of codewords by codebooks may be different according to the diagnostic importance of the corresponding image region. This permits to create appropriate codebooks with representative codewords, and to obtain good reconstruction quality in relevant zones, while reinforcing compression in less important regions. The proposed approach is tested on ultrasound esophagus images and is shown to be very promising.