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

34 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)54-63
Number of pages10
JournalIEEE Transactions on Information Technology in Biomedicine
Volume7
Issue number1
DOIs
Publication statusPublished - 2003 Mar 1

Fingerprint

Data Compression
Wavelet Analysis
Telemedicine
Data compression
Data communication systems
Wavelet transforms
Computer Communication Networks
Trees (mathematics)
Signal-To-Noise Ratio
Telecommunication networks
Signal to noise ratio
Specifications

Keywords

  • Image coding
  • Telemedical communication network
  • Wavelet transform

ASJC Scopus subject areas

  • Health Informatics
  • Health Information Management
  • Information Systems
  • Computer Science Applications
  • Computational Theory and Mathematics

Cite this

Scalable medical data compression and transmission using wavelet transform for telemedicine applications. / Hwang, Wen Jyi; Chine, Ching Fung; Li, Kuo Jung.

In: IEEE Transactions on Information Technology in Biomedicine, Vol. 7, No. 1, 01.03.2003, p. 54-63.

Research output: Contribution to journalArticle

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