In early April 2023, Meta AI released Segment Anything (SAM), an machine-learning based segmentation model. The repository model of SAM operates on a very general image database, so we have been re-training SAM to specifically process mammograms and identify any abnormalities within. In 2020, it is estimated that there were roughly 2.3 million new cases of breast cancer, and one of the detection methods is using mammograms to visualize potentially cancerous abnormalities. The goal is to train SAM to automatically detect and annotate abnormalities in mammograms with the intent of processing mammograms with greater than current accuracy and speed.

The repository version of SAM is a parameterized predictive model, which only uses the information provided by Meta AI to create parameters which guide SAM to identifying and segmenting different image components. Currently, we are working on training SAM specifically onmammograms so we can add and change parameters to more specifically focus on breast cancer detection. The expectation is that SAM will soon be able to identify abnormalities in a mammogram, soon after annotate those abnormalities to determine what they are (cancer, mineral deposits, healthy tissue, etc.). As we progress, the expectation is that after specifically identifying cancer or cancer-related abnormalities in mammograms, the SAM model can be expanded to other tissues and their screening for cancer.