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Scatter compensation for digital chest radiography using maximum likelihood expectation maximization
C E Floyd1, A H Baydush, J Y Lo
1Department of Biomedical Engineering, Duke University Medical Center, Durham, North Carolina 27710.
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 scatter-reduced 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 (6.4% 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 108% and SNR was improved by 10%. In the retrocardiac region, contrast was increased 180% while SNR decreased by 6%.
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.