AutoCumulus: an automated mammographic density measure created using artificial intelligence.

Osamah Al-Qershi; Tuong L Nguyen; Michael S Elliott; Daniel F Schmidt; Enes Makalic; Shuai Li; Samantha K Fox; James G Dowty; Carlos A Peña-Solorzano; Chun Fung Kwok; Yuanhong Chen; Chong Wang; Jocelyn Lippey; Peter Brotchie; Gustavo Carneiro; Davis J McCarthy; Yeojin Jeong; Joohon Sung; Helen ML Frazer; John L Hopper

Journal article

AutoCumulus: an automated mammographic density measure created using artificial intelligence.

Osamah Al-Qershi, Tuong L Nguyen, Michael S Elliott, Daniel F Schmidt, Enes Makalic, Shuai Li, Samantha K Fox, James G Dowty, Carlos A Peña-Solorzano, Chun Fung Kwok, Yuanhong Chen, Chong Wang, Jocelyn Lippey, Peter Brotchie, Gustavo Carneiro, Davis J McCarthy, Yeojin Jeong, Joohon Sung, Helen ML Frazer, John L Hopper

BMC Cancer | Published : 2026

DOI: 10.1186/s12885-026-16264-z

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..

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