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 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.

Duke Scholars

Author Joseph Yuan-Chieh Lo Radiology

Author Carl Eric Ravin Radiology, Cardiothoracic Imaging