Scalable medical data compression and transmission using wavelet transform for telemedicine applications

Wen-Jyi Hwang, Ching Fung Chine, Kuo Jung Li

Research output: Contribution to journalArticle

35 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)54-63
Number of pages10
JournalIEEE Transactions on Information Technology in Biomedicine
Issue number1
Publication statusPublished - 2003 Mar 1



  • Image coding
  • Telemedical communication network
  • Wavelet transform

ASJC Scopus subject areas

  • Biotechnology
  • Computer Science Applications
  • Electrical and Electronic Engineering

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