A region of interest (ROI) based wavelet compression scheme for medical images

In this paper, we present a novel method for selective compression of medical images. In our scheme, regions of interest (ROIs) are differentiated from the background by detecting relevant features such as edges, texture and clusters. A detection map is created for ROIs so that the coding system can use it to assign proper bit rates in the process of quantization. The localized, multiresolution representation of the wavelet coefficients makes it easy to allocate different bit rates to complex, adjacent ROIs in the process of successive approximation quantization (SAQ) of wavelet coefficients. For maximum flexibility and efficiency in selective allocation of bit rates, we use an intraband coding scheme, compact quadtree (CQT)[22], instead of the conventional interband approaches. By adjusting the amplitudes of the wavelet coefficients in ROIs, one can smoothly preserve multiple ROIs with victual no coding overhead. Experimental results on digital mammographical images show that minute microcalcifications can be perfectly preserved while their background is compressed at very high ratios, i.e., over 100 to 1.