Image reconstruction for a stationary digital breast tomosynthesis system

Abstract

We have designed and built a stationary digital breast tomosynthesis (DBT) system containing a carbon nanotube based field emission x-ray source array to examine the possibility of obtaining a reduced scan time and improved image quality compared to conventional DBT systems. There are 25 individually addressable x-ray sources in our linear source array that are evenly angularly spaced to cover an angle of 48°. The sources are turned on sequentially during imaging and there is no motion of either the source or the detector. We present here an iterative reconstruction method based on a modified Ordered-Subset Convex (MOSC) algorithm that was employed for the reconstruction of images from the new DBT system. Using this algorithm based on a maximum-likelihood model, we reconstruct on non-cubic voxels for increased computational efficiency resulting in high in-plane resolution in the images. We have applied the reconstruction technique on simulated and phantom data from the system. Even without the use of the subsets, the reconstruction of an experimental 9-beam system with 960x768 pixels took less than 6 minutes (10 iterations). The projection images of a simulated mammography accreditation phantom were reconstructed using MOSC and a Simultaneous Algebraic Reconstruction technique (SART) and the results from the comparison between the two algorithms allow us to conclude that the MOSC is capable of delivering excellent image quality when used in tomosynthesis image reconstruction.