Progressive ROI coding and diagnostic quality for medical image compression

This work addresses the delicate problem of lossy compression of medical images. More specifically, a selective allocation of coding resources is introduced based on the concept of 'diagnostic interest' and an interactive methodology based on a new measure of 'diagnostic quality'. The selective allocation of resources is made possible by a selection a priori of regions of specific interest for diagnostic purpose. The idea is to change the precision of representation in a transformed domain of region of particular interest, through a weighting procedure by an on- line user-defined quantization matrix. The overall compression method is multi-resolution, provides for an embedded generation of the bit-stream and guarantees for a good rate distortion trade-off, at various bit-rates, with spatially varying reconstruction quality. This work also analyzes the delicate issue of a professional usage of lossy compression in a PACS environment. The proposed compression methodology gives interesting insights in favor of using lossy compression in a controlled fashion by the expert radiologist. Most of the ideas presented in this work have been confirmed by extensive experimental simulations involving medical expertise.