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Proceedings Paper

Subjective assessment of high-level image compression of digitized mammograms
Author(s): J. Ken Leader; Jules H. Sumkin; Marie A. Ganott; Christiane M. Hakim; Lara A. Hardesty; Ratan Shah; Luisa Wallace; Amy H. Klym; John M. Drescher; Glenn S. Maitz; David Gur
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Paper Abstract

This study was designed to evaluate radiologists’ ability to identify highly-compressed, digitized mammographic images displayed on high-resolution, monitors. Mammography films were digitized at 50 micron pixel dimensions using a high-resolution laser film digitizer. Image data were compressed using the irreversible (lossy), wavelet-based JPEG 2000 method. Twenty images were randomly presented in pairs (one image per monitor) in three modes: mode 1, non-compressed versus 50:1 compression; mode 2, non-compressed versus 75:1 compression; and mode 3, 50:1 versus 75:1 compression with 20 random pairs presented twice (80 pairs total). Six radiologists were forced to choose which image had the lower level of data compression in a two-alternative forced choice paradigm. The average percent correct across the six radiologists for modes 1, 2 and 3 were 52.5% (+/-11.3), 58.3% (+/-14.7), and 58.3% (+/-7.5), respectively. Intra-reader agreement ranged from 10 to 50% and Kappa from -0.78 to -0.19. Kappa for inter-reader agreement ranged from -0.47 to 0.37. The “monitor effect” (left/right) was of the same order of magnitude as the radiologists’ ability to identify the lower level of image compression. In this controlled evaluation, radiologists did not accurately discriminate non-compressed and highly-compressed images. Therefore, 75:1 image compression should be acceptable for review of digitized mammograms in a telemammography system.

Paper Details

Date Published: 4 May 2004
PDF: 8 pages
Proc. SPIE 5372, Medical Imaging 2004: Image Perception, Observer Performance, and Technology Assessment, (4 May 2004); doi: 10.1117/12.533201
Show Author Affiliations
J. Ken Leader, Univ. of Pittsburgh (United States)
Jules H. Sumkin, Univ. of Pittsburgh (United States)
Magee-Women's Hospital (United States)
Marie A. Ganott, Univ. of Pittsburgh (United States)
Magee-Women's Hospital (United States)
Christiane M. Hakim, Univ. of Pittsburgh (United States)
Magee-Women's Hospital (United States)
Lara A. Hardesty, Univ. of Pittsburgh (United States)
Magee-Women's Hospital (United States)
Ratan Shah, Univ. of Pittsburgh (United States)
Magee-Women's Hospital (United States)
Luisa Wallace, Univ. of Pittsburgh (United States)
Magee-Women's Hospital (United States)
Amy H. Klym, Univ. of Pittsburgh (United States)
John M. Drescher, Univ. of Pittsburgh (United States)
Glenn S. Maitz, Univ. of Pittsburgh (United States)
David Gur, Univ. of Pittsburgh (United States)


Published in SPIE Proceedings Vol. 5372:
Medical Imaging 2004: Image Perception, Observer Performance, and Technology Assessment
Dev P. Chakraborty; Miguel P. Eckstein, Editor(s)

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