Automated Lugano Metabolic Response Assessment in 18 F-Fluorodeoxyglucose-Avid Non-Hodgkin Lymphoma With Deep Learning on 18 F-Fluorodeoxyglucose-Positron Emission Tomography.

Skander JemaaSouhila OunadjelaXiaoyong WangTarec C El-GalalyLale KostakogluAndrea KnappGrace KuLisa MusickDenis SahinMichael C WeiShen YinThomas BengtssonAlex De CrespignyRichard A D Carano

Published in: Journal of clinical oncology : official journal of the American Society of Clinical Oncology (2024)

These results suggest that the proposed method can be incorporated into radiologic response assessment workflows in cancer imaging for significant time savings and with performance similar to trained medical experts.

Keyphrases

positron emission tomography
computed tomography
deep learning
pet ct
pet imaging
machine learning
papillary thyroid
healthcare
high resolution
artificial intelligence
high throughput
resistance training
high intensity
fluorescence imaging