title: Scalable medical data compression and transmission using wavelet transform for telemedicine applications.
abstract: In this paper, a novel medical data compression algorithm, termed layered set partitioning in hierarchical trees (LSPIHT) algorithm, is presented for telemedicine applications. 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, we can reconstruct medical data with various signal-to-noise ratios (SNRs) and/or resolutions. Receivers with distinct specifications can then share the same source encoder to reduce the complexity of telecommunication networks for telemedicine applications. Numerical results show that, besides having low network complexity, the LSPIHT attains better rate-distortion performance as compared with other algorithms for encoding medical data.
authors.affiliation: Department of Electrical Engineering, Chung Yuan Christian University, Chungli, 32023, Taiwan. whwang@dec.ee.cycu.edu.tw
authors.forename: Wen-Jyi
authors.initials: WJ
authors.lastname: Hwang
authors.forename: Ching-Fung
authors.initials: CF
authors.lastname: Chine
authors.forename: Kuo-Jung
authors.initials: KJ
authors.lastname: Li
mesh_terms: D000465:Algorithms; D008279:Magnetic Resonance Imaging; D017216:Telemedicine / Q000379:methods*