Breast density and parenchymal patterns have been studied extensively and found to be useful for assessing the risk of developing breast cancer, according to lead author Dr. Hui Li, PhD.
"By assessing women's risk of developing breast cancer, it will allow physicians to [provide] better patient management and potentially lead to precision medicine," Li told AuntMinnie.com.
The researchers found that deep learning appears to be able to extract textural characteristics directly from full-field digital mammograms as well as or better than conventional texture analysis in distinguishing between cancer-risk populations.
"It has potential to help clinicians in assessing mammographic parenchymal patterns for breast cancer risk assessment," he said.
What else did the group find? Attend the early-morning talk on Monday for all of the details.
