MRI-based patient selection for active surveillance in prostate cancer using U-Found: a generalized deep learning model

Abstract Background Current MRI prostate cancer risk assessment methods focus mainly on detecting tumor lesions, ignoring the prostate gland macro-environment which may also impact disease progression. A generalized deep-learning model for prostate may help capture these gland-level characteristics...

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Κύριοι συγγραφείς:	Noah C. Lowry, Adrian L. Breto, Veronica Wallaengen, Ahmad Algohary, Nicolas Tapia-Stoll, Sandra M. Gaston, Nachiketh S. Prakash, Pedro F. S. Freitas, Oleksandr N. Kryvenko, Patricia Castillo, Joel Saltz, Tahsin Kurc, Chad R. Ritch, Bruno Nahar, Mark L. Gonzalgo, Dipen J. Parekh, Brandon Mahal, Benjamin O. Spieler, Alan Dal Pra, Matthew C. Abramowitz, Alan Pollack, Sanoj Punnen, Radka Stoyanova
Μορφή:	Artigo
Γλώσσα:	Inglês
Έκδοση:	BMC 2026-01-01
Σειρά:	Cancer Imaging
Θέματα:	Deep learning Foundation models Contrastive learning Unsupervised deep learning Prostate cancer Active Surveillance
Διαθέσιμο Online:	https://doi.org/10.1186/s40644-026-00988-z
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