Experimental investigation of iterative reconstruction techniques for high resolution mammography

Abstract

The further development of the new iterative reconstruction algorithms to improve three-dimensional breast images quality restored from incomplete and noisy mammograms, is provided. The algebraic reconstruction method with simultaneous iterations – Simultaneous Algebraic Reconstruction Technique (SART) and the iterative method of statistical reconstruction Bayesian Iterative Reconstruction (BIR) are referred here as the preferable iterative methods suitable to improve the image quality. For better processing we use the Graphics Processing Unit (GPU). Method of minimizing the Total Variation (TV) is used as a priori support for regularization of iteration process and to reduce the level of noise in the reconstructed image. Preliminary results with physical phantoms show that all examined methods are capable to reconstruct structures layer-by-layer and to separate layers which images are overlapped in the Z- direction. It was found that the method of traditional Shift-And-Add tomosynthesis (SAA) is worse than iterative methods SART and BIR in terms of suppression of the anatomical noise and image blurring in between the adjacent layers. Despite of the fact that the measured contrast/noise ratio in the presence of low contrast internal structures is higher for the method of tomosynthesis SAA than for SART and BIR methods, its effectiveness in the presence of structured background is rather poor. In our opinion the optimal results can be achieved using Bayesian iterative reconstruction BIR.