Our initial dataset of 176, 492 mammograms contained an estimated 5.5% lower quality scans with issues like metal coil frames, wire clamps, and breast implants. Manually removing these images is tedious and error-prone. Our two-stage process first uses threshold-based 5-bin histogram filtering to eliminate undesirable images, followed by a variational autoencoder to remove remaining low-quality scans. Our method detects such scans with an F1 Score of 0.8862 and preserves 163, 568 high-quality mammograms. We provide results and tools publicly available as open-source software, available here: https://github.com/mpsych/ODM