Reconstruction-Independent 3D CAD for Calcification Detection in Digital Breast Tomosynthesis Using Fuzzy Particles

In this paper we present a novel approach for microcalcification detection in Digital Breast Tomosynthesis (DBT) datasets. A reconstructionindependent approach, working directly on the projected views, is proposed. Wavelet filter responses on the projections are thresholded and combined to obtain candidate microcalcifications. For each candidate, we create a fuzzy contour through a multi-level thresholding process. We introduce a fuzzy set definition for the class microcalcification contour that allows the computation of fuzzy membership values for each candidate contour. Then, an aggregation operator is presented that combines information over the complete set of projected views, resulting in 3D fuzzy particles. A final decision is made taking into account information acquired over a range of successive processing steps. A clinical example is provided that illustrates our approach. DBT still being a new modality, a similar published approach is not available for comparison and limited clinical data currently prevents a clinical evaluation of the algorithm. .