Quantitative performance evaluation of the EM algorithm applied to radiographic images

James C. Brailean; Maryellen Lissak Giger; Chin-Tu Chen; Barry J. Sullivan

doi:10.1117/12.44283

1 July 1991 Quantitative performance evaluation of the EM algorithm applied to radiographic images

James C. Brailean, Maryellen Lissak Giger, Chin-Tu Chen, Barry J. Sullivan

Proceedings Volume 1450, Biomedical Image Processing II; (1991) https://doi.org/10.1117/12.44283
Event: Electronic Imaging '91, 1991, San Jose, CA, United States

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.

Citation Download Citation

James C. Brailean, Maryellen Lissak Giger, Chin-Tu Chen, and Barry J. Sullivan "Quantitative performance evaluation of the EM algorithm applied to radiographic images", Proc. SPIE 1450, Biomedical Image Processing II, (1 July 1991); https://doi.org/10.1117/12.44283

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