The Non-prewhitening and Hotelling Observers for Parameter Selection for Linear Iterative Image Reconstruction in Breast Tomosynthesis

Abstract

Digital breast tomosynthesis (DBT) has seen widespread clinical adoption for breast cancer screening over the past decade as either a supplement to, or replacement for, digital mammography. As in computed tomography, iterative image reconstruction methods for DBT involve specification of a large number of parameters that can significantly impact image quality. Efficiently computable task-based metrics are needed for characterizing the parameter dependencies of these reconstruction methods. Here we investigate two task-based image quality metrics for assessing the effect of regularization strength on microcalcification detectability for an iterative reconstruction method in DBT.