Applications Of High Compression Coding To Dynamic Medical Image Series

Abstract

The successful implementation of medical PACS requires the use of powerful compression coding to archive and transmit images and image series. In this prospect, we developed and evaluated a general irreversible method to compress medical image series achieving compression ratios as high as 50:1 to 100:1. The implemented technique combines two coding schemes which multiply their effects. A principal component analysis, first step of the conventional factor analysis of dynamic structures (FADS), is applied to the original dynamic series. A limited number of principal components (curves) and their associated spatial distribution (images) are computed. Then, each image is compressed by using an adaptive block-quantization technique computing the 2D discrete cosine transform (DCT). To reconstruct the images associated to the principal components, an inverse DCT is applied. Then, the original series is computed from the reconstructed images combined with the principal components, stored without any modification. The reconstructed series is compared to the original one, as well as the time-activity curves generated using different regions of interests (ROI) and the results obtained applying FADS to the two series.