Image for representation purpose only. Credit: Wikimedia Commons
The estimation of breast density using a deep learning model has the potential to enhance the prediction of breast cancer risk. Breast density is a crucial factor in determining the likelihood of developing breast cancer, as women with denser breasts have a higher risk of developing this disease.
Traditionally, the assessment of breast density has relied on subjective visual interpretation by radiologists when reviewing mammograms. However, deep learning models can automate this process by precisely evaluating digital mammograms to quantify breast density.
The University of Manchester has been actively researching the use of deep-learning models for breast density estimation. Their recent study, published in Scientific Reports, presented a deep learning model that achieved high accuracy in estimating breast density. The model was trained on mammograms from over 10,000 women and successfully classified breast density into one of four categories.
Utilizing deep learning models for breast density assessment could improve the identification of women at a higher risk of developing breast cancer, enabling earlier detection and treatment. Ultimately, this advancement has the potential to save lives and enhance the outcomes of women with breast cancer.