Compression / decompression strategies for large volume medical imagery

We present a scheme for compressed domain interactive rendering of large volume data sets over distributed environments. The scheme exploits the distortion scalability and multi-resolution properties offered by JPEG2000 to provide a unified framework for interactive rendering over low bandwidth networks. The interactive client is provided breadth in terms of scalability in resolution, position and progressive improvement by quality. The server exploits the spatial locality offered by the DWT and packet indexing information to transmit, in so far as possible, compressed volume data relevant to the clients query. Once the client identifies its volume of interest (VOI), the volume is refined progressively within the VOI. Contextual background information can also be made available having quality fading away from the VOI. The scheme is ideally suited for client-server setups with low bandwidth constraints, with the server maintaining the compressed volume data, to be browsed by a client with low processing power and/or memory. Rendering can be performed at a stage when the client feels that the desired quality threshold has been attained. We investigate the effects of code-block size on compression ratio, PSNR, decoding times and data transmission to arrive at an optimal code-block size for typical VOI decoding scenarios.