The reconstruction of a volumetric image from Digital Breast Tomosynthesis (DBT) measurements is an ill-posed inverse problem, for which existing iterative regularized approaches can provide a good solution. However, the clinical task is somehow omitted in the derivation of those techniques, although it plays a primary role in the radiologist diagnosis. In this work, we address this issue by introducing a novel variational formulation for DBT reconstruction, tailored for a specific clinical task, namely the detection of microcalcifications. Our method aims at simultaneously enhancing the detectability performance and enabling a high-quality restoration of the background breast tissues. Our contribution is threefold. First, we introduce an original task-based reconstruction framework through the proposition of a detectability function inspired from mathematical model observers. Second, we propose a novel total-variation regularizer where the gradient field accounts for the different morphological contents of the imaged breast. Third, we integrate the two developed measures into a cost function, minimized thanks to a new form of the Majorize Minimize Memory Gradient (3MG) algorithm. We conduct a numerical comparison of the convergence speed of the proposed method with those of standard convex optimization algorithms. Experimental results show the interest of our DBT reconstruction approach, qualitatively and quantitatively.

We propose a novel approach aimed to improve the detectability of microcalcifications in Digital Breast Tomosynthesis (DBT) volumes. Hence, our contribution is twofold. First, we formulate the clinical task through a detectability function based on an approach inspired from mathematical model observers. Second, we integrate this new developed clinical-task term in a cost function which is minimized for 3D reconstruction of DBT volumes. Experimental results carried out on both phantom and real clinical data show that the proposed clinical term allows the visibility of microcalcifications to be significantly improved, while preserving an overall high quality of the fully reconstructed volume.

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