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Proceedings Paper

Quantitative performance evaluation of the EM algorithm applied to radiographic images
Author(s): James C. Brailean; Maryellen Lissak Giger; Chin-Tu Chen; Barry J. Sullivan
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Paper Abstract

In this study, the authors evaluate quantitatively the performance of the Expectation Maximization (EM) algorithm as a restoration technique for radiographic images. The 'perceived' signal-to-nose ratio (SNR), of simple radiographic patterns processed by the EM algorithm are calculated on the basis of a statistical decision theory model that includes both the observer's visual response function and a noise component internal to the eye-brain system. The relative SNR (ratio of the processed SNR to the original SNR) is calculated and used as a metric to quantitatively compare the effects of the EM algorithm to two popular image enhancement techniques: contrast enhancement (windowing) and unsharp mask filtering.

Paper Details

Date Published: 1 July 1991
PDF: 7 pages
Proc. SPIE 1450, Biomedical Image Processing II, (1 July 1991); doi: 10.1117/12.44283
Show Author Affiliations
James C. Brailean, Northwestern Univ. (United States)
Maryellen Lissak Giger, Univ. of Chicago (United States)
Chin-Tu Chen, Univ. of Chicago (United States)
Barry J. Sullivan, Northwestern Univ. (United States)


Published in SPIE Proceedings Vol. 1450:
Biomedical Image Processing II
Alan Conrad Bovik; Vyvyan Howard, Editor(s)

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