Clinical evaluation of wavelet compression of digitized chest x-rays

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

1 Scopus citations

Abstract

In this paper we assess lossy image compression of digitalized chest x-rays using radiologist assessment of anatomic structures and numerical measurements of image accuracy. Forty chest x-rays were digitized and compressed using an irreversible wavelet technique at 10, 20, 40 and 80:1. These were presented in a blinded fashion with an uncompressed image for subjective A-B comparison of 11 anatomic structures as well as overall quality. Mean error, RMS error, maximum pixel error, and number of pixels within 1 percent of original value were also computed for compression ratios from 10:1 to 80:1. We found that at low compression there was a slight preference for compressed images. There was no significant difference at 20:1 and 40:1. There was a slight preference on some structures for the original compared with 80:1 compressed images. Numerical measures demonstrated high image faithfulness, both in terms of number of pixels that were within 1 percent of their original value, and by the average error for all pixels. Our findings suggest that lossy compression at 40:1 or more can be used without perceptible loss in the demonstration of anatomic structures.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
PublisherSociety of Photo-Optical Instrumentation Engineers
Pages312-317
Number of pages6
ISBN (Print)0819424420
StatePublished - 1997
EventMedical Imaging 1997: Image Display - Newport Beach, CA, USA
Duration: Feb 23 1997Feb 25 1997

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume3031
ISSN (Print)0277-786X

Other

OtherMedical Imaging 1997: Image Display
CityNewport Beach, CA, USA
Period2/23/972/25/97

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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