{'fraction_non_alphanumeric': 0.015165876777251185, 'fraction_numerical': 0.0037914691943127963, 'mean_word_length': 5.478527607361963, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A reconstruction-independent method for computerized mass detection in digital tomosynthesis images of the breast

We developed a two-stage computerized mass detection algorithm for digital tomosynthesis images of the breast. Rather than analyze the reconstructed 3D breast volume, our algorithm operates on each of the 2D projection images directly. We chose this approach because reconstruction algorithms for breast tomosynthesis are still being optimized, which can alter the appearance of the 3D reconstructed breast volume. Furthermore this approach allows us to take advantage of mass detection methods already developed for conventional two-view projection mammography, which are similar to projection images for digital tomosynthesis. We applied our algorithm to two tomosynthesis image sets, one of which was a computer simulated 3D breast phantom, and one was a clinical image set. In both cases, the lesion was detected in the first stage of the algorithm, while the second stage of the algorithm efficiently reduced false positive detections.