A memory-assisted lossless compression algorithm for medical images

Abstract

Rapid growth of emerging medical applications such as e-health and tele-medicine requires fast, low cost, and often lossless access to massive amount of medical images and data over bandlimited channels. In this paper, we first show that significant amount of correlation and redundancy exist across different medical images. Such a correlation can be utilized to achieve better compression, and consequently less storage and less communication overhead on the network. We propose a novel memory-assisted compression technique, as a learning-based universal coding, which can be used to complement any existing algorithm to further eliminate redundancies across images. The approach is motivated by t..