Improved image quality with Bayesian image processing in digital mammography

Recent developments in digital detectors have led to investigating the importance of grids in mammography. We propose to examine the use Bayesian Image Estimation (BIE) as a software means of removing scatter post acquisition and to compare this technique to a grid. BIE is an iterative, non-linear statistical estimation technique that reduces scatter content while improving CNR. Images of the ACR breast phantom were acquired both with and without a grid on a calibrated digital mammography system. A BIE algorithm was developed and was used to process the images acquired without the grid. Scatter fractions (SF) were compared for the image acquired with the grid, the image acquired without the grid, and the image acquired without the grid and processed by BIE. Images acquired without the anti-scatter grid had an initial SF of 0.46. Application of the Bayesian image estimation technique reduced this to 0.03. Tn comparison, the use of the grid reduced the SF to 0.19. The use of Bayesian image estimation in digital mammography is beneficial in reducing scarcer fractions. This technique is very useful as it can reduce scatter content effectively without introducing any adverse effects such as aliasing caused by gridlines.