RATIONALE AND OBJECTIVES.An iterative maximum likelihood expectation maximization algorithm (MLEM) has been developed for scatter compensation in chest radiography.METHODS.The MLEM technique produces a scatterreduced image which maximizes the probability of observing the measured image. We examined the scatter content and the low-contrast signal-to-noise ratio (SNR) in digital radiographs of anatomical phantoms before and after compensation.RESULTS.MLEM converged to an accurate (6.4percnt;RMS residual scatter error) estimate within 12 iterations. Both contrast and noise were increased in the processed images as iteration progressed. In the lung, contrast was increased 108percnt; and SNR was improved by 10percnt;. In the retrocardiac region, contrast was increased 180percnt; while SNR decreased by 6percnt;.CONCLUSIONS.This is the first report of a post-acquisition scatter compensation technique which can increase SNR. These results suggest that statistical estimation techniques can enhance image quality and quantitative accuracy for digital chest radiography.
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