SCATTER COMPENSATION FOR DIGITAL CHEST RADIOGRAPHY USING MAXIMUM-LIKELIHOOD EXPECTATION MAXIMIZATION

RATIONALE AND OBJECTIVES. An iterative maximum likelihood expectation maximization algorithm (MLEM) has been developed for scatter compensat ion in chest radiography. METHODS. The MLEM technique produces a scatt er-reduced image which maximizes the probability of observing the meas ured image. We examined the scatter content and the low-contrast signa l-to-noise ratio (SNR) in digital radiographs of anatomical phantoms b efore and after compensation. RESULTS. MLEM converged to an accurate ( 6.4%RMS residual scatter error) estimate within 12 iterations. Both co ntrast and noise were increased in the processed images as iteration p rogressed. In the lung, contrast was increased 108% and SNR was improv ed by 10%. In the retrocardiac region, contrast was increased 180% whi le SNR decreased by 6%. CONCLUSIONS. This is the first report of a pos t-acquisition scatter compensation technique which can increase SNR. T hese results suggest that statistical estimation techniques can enhanc e image quality and quantitative accuracy for digital chest radiograph y.