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
CountryCanada
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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