Medical image analysis and data compression are rapidly evolving fields with growing applications in healthcare services e.g. teleradiology, teleconsultation, e-health, telemedicine and statistical analysis of medical data. In this paper, a Layered Set Partitioning in Hierarchical Trees (LSPIHT) algorithm for medical data compression and transmission is presented. In the LSPIHT, the encoded bit streams are divided into a number of layers for transmission and reconstruction. Starting from the base layer, by accumulating bit streams up to different enhancement layers, medical data can be reconstructed with various signal-to-noise ratios (SNRs) and resolutions. Receivers with distinct specifications can then share the same source encoder to reduce the complexity of telecommunication networks for telemedicine applications. The algorithm is compared with other algorithms for encoding ECG data, and analysis shows that the LSPIHT attains better rate-distortion performance and low network complexity than other encoding techniques.DOI: http://dx.doi.org/10.3329/dujs.v60i1.10332 Dhaka Univ. J. Sci. 60(1): 31-36, 2012 (January)
Medical Data Compression and Transmission in Noisy WLANS: A Review
