Deep learning‐based quantification of PET/CT prostate gland uptake: association with overall survival

AIM: To validate a deep‐learning (DL) algorithm for automated quantification of prostate cancer on positron emission tomography/computed tomography (PET/CT) and explore the potential of PET/CT measurements as prognostic biomarkers. MATERIAL AND METHODS: Training of the DL‐algorithm regarding prostat...

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Detalles Bibliográficos
Autores principales: Polymeri, Eirini, Sadik, May, Kaboteh, Reza, Borrelli, Pablo, Enqvist, Olof, Ulén, Johannes, Ohlsson, Mattias, Trägårdh, Elin, Poulsen, Mads H., Simonsen, Jane A., Hoilund‐Carlsen, Poul Flemming, Johnsson, Åse A., Edenbrandt, Lars
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7027436/
https://www.ncbi.nlm.nih.gov/pubmed/31794112
http://dx.doi.org/10.1111/cpf.12611

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7027436/
https://www.ncbi.nlm.nih.gov/pubmed/31794112
http://dx.doi.org/10.1111/cpf.12611

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