Practical iterative image reconstruction in digital breast tomosynthesis by non-convex TpV optimization

Digital breast tomosynthesis (DBT) is a rapidly developing imaging modality that gives some tomographic information for breast cancer screening. The effectiveness of standard mammography can be limited by the presence of overlapping structures in the breast. A DBT scan, consisting of a limited number of views covering a limited arc projecting the breast onto a fixed flat-panel detector, involves only a small modification of digital mammography, yet DBT yields breast image slices with reduced interference from overlapping breast tissues. We have recently developed an iterative image reconstruction algorithm for DBT based on image total variation (TV) minimization that improves on EM in that the resulting images have fewer artifacts and there is no need for additional regularization. In this abstract, we present the total p-norm variation (TpV) image reconstruction algorithm. TpV has the advantages of our previous TV algorithm, while improving substantially on the efficiency. Results for the TpV on clinical data are shown and compared with EM.