Exploring the effects of compression via principal components analysis on X-ray image cassification

Vikash Rameshar, Wesley Doorsamy

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

Image compression in medical applications implores careful consideration of the effects on data veracity. The inexorable challenge of assessing the volume-veracity trade-off is becoming more prevalent in this critical application area, and particularly when machine learning is used for the purpose of assisted diagnostics. This paper investigates the impact of compressing X-ray images on the accuracy of fracture diagnostics. The accuracy of the classification system is assessed for X-ray images of both healthy and fracture bones when subjected to different levels of compression. Compression is achieved using principal components analysis. Results indicate that accuracy is only marginally affected under a level one compression but begins to deteriorate under level two compression. These results are potentially useful as the level one compression yields gains up to 94% with less than a 2% drop in classification accuracy.

Original languageEnglish
Title of host publication2019 6th International Conference on Soft Computing and Machine Intelligence, ISCMI 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages150-154
Number of pages5
ISBN (Electronic)9781728145778
DOIs
Publication statusPublished - Nov 2019
Event6th International Conference on Soft Computing and Machine Intelligence, ISCMI 2019 - Johannesburg, South Africa
Duration: 19 Nov 201920 Nov 2019

Publication series

Name2019 6th International Conference on Soft Computing and Machine Intelligence, ISCMI 2019

Conference

Conference6th International Conference on Soft Computing and Machine Intelligence, ISCMI 2019
Country/TerritorySouth Africa
CityJohannesburg
Period19/11/1920/11/19

Keywords

  • Big data
  • Compression
  • Image classification
  • Principal component analysis
  • X-ray

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Computational Mathematics
  • Modeling and Simulation

Fingerprint

Dive into the research topics of 'Exploring the effects of compression via principal components analysis on X-ray image cassification'. Together they form a unique fingerprint.

Cite this