Prediction of disease severity in COPD: a deep learning approach for anomaly-based quantitative assessment of chest CT - Almeida, Silvia D.; Norajitra, Tobias; Lüth, Carsten T.; Wald, Tassilo; Weru, Vivienn; Nolden, Marco; Jäger, Paul F.; Stackelberg, Oyunbileg von; Heußel, Claus Peter; Weinheimer, Oliver; Biederer, Jürgen; Kauczor, Hans-Ulrich; et al. (European radiology, 2024)
To quantify regional manifestations related to COPD as anomalies from a modeled distribution of normal-appearing lung on chest CT using a deep learning (DL) approach, and to assess its potential to predict disease severity.