AutoCumulus: an automated mammographic density measure created using artificial intelligence

Abstract

Background: Mammographic (or breast) density is an established risk factor for breast cancer, previously measured using a variety of quantitative, semi-automated and automated approaches. We present a new automated measure, AutoCumulus, learned from applying deep learning to semi-automated measures. Methods: We studied the mammograms of 9,057 population-screened women in the BRAIx program for which semi-automated measurements of mammographic density had been made by experienced readers using the CUMULUS software. The dataset was split into training, testing, and validation sets (80%, 10%, and 10%, respectively). We applied a deep learning regression model (fine-tuned ConvNeXtSmall) to estima..