Burrows-Wheeler Transformation for Medical Image Compression

Aierken Shalayiding, Ziya Arnavut, Basar Koc, Huseyin Kocak

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Medical imaging is a very useful component in diagnosing diseases. For future use, and further study and analysis, hospitals must keep all patients' medical images in databases. In this work, a new lossless image compression technique is proposed for efficient storage and transmission of medical images. The newly proposed technique is based on encoding prediction errors with a suitable entropy coder upon transforming them with the Burrows-Wheeler Transformation (BWT). We show that the newly proposed technique yields better compression than the mainstream lossless compression algorithms JPEG-2000 and JPEG-LS.

Original languageEnglish (US)
Title of host publication11th Annual IEEE Information Technology, Electronics and Mobile Communication Conference, IEMCON 2020
EditorsRajashree Paul
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages723-727
Number of pages5
ISBN (Electronic)9781728184166
DOIs
StatePublished - Nov 4 2020
Externally publishedYes
Event11th Annual IEEE Information Technology, Electronics and Mobile Communication Conference, IEMCON 2020 - Virtual, Vancouver, Canada
Duration: Nov 4 2020Nov 7 2020

Publication series

Name11th Annual IEEE Information Technology, Electronics and Mobile Communication Conference, IEMCON 2020

Conference

Conference11th Annual IEEE Information Technology, Electronics and Mobile Communication Conference, IEMCON 2020
Country/TerritoryCanada
CityVirtual, Vancouver
Period11/4/2011/7/20

Keywords

  • BWIC
  • Burrows-Wheeler Transformation (BWT)
  • JPEG-2000
  • JPEG-LS
  • Medical image compression

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems and Management
  • Electrical and Electronic Engineering
  • Health Informatics

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