Spatial Matching of 2D Mammography Images and Specimen Radiographs: Towards Improved Characterization of Suspicious Microcalcifications
This work addresses the challenge of improving diagnostic accuracy for breast cancer detection by enabling joint characterization of microcalcifications and surrounding tissue, though it is incremental as it builds on existing template matching methods.
The paper tackled the problem of accurately characterizing suspicious microcalcifications in breast tissue by developing a template matching-based approach to spatially match 2D mammography images with specimen radiographs, achieving a high negative predictive value of 0.98 but modest precision of 0.66 and recall of 0.58.
Accurate characterization of suspicious microcalcifications is critical to determine whether these calcifications are associated with invasive disease. Our overarching objective is to enable the joint characterization of microcalcifications and surrounding breast tissue using mammography images and digital histopathology images. Towards this goal, we investigate a template matching-based approach that utilizes microcalcifications as landmarks to match radiographs taken of biopsy core specimens to groups of calcifications that are visible on mammography. Our approach achieved a high negative predictive value (0.98) but modest precision (0.66) and recall (0.58) in identifying the mammographic region where microcalcifications were taken during a core needle biopsy.