Anatomically guided self-adapting deep neural network for clinically significant prostate cancer detection on bi-parametric MRI: a multi-center study
Abstract Objective To evaluate the effectiveness of a self-adapting deep network, trained on large-scale bi-parametric MRI data, in detecting clinically significant prostate cancer (csPCa) in external multi-center data from men of diverse demographics; to investigate the advantages of transfer learn...
Salvato in:
| Autori principali: | , , , , , , |
|---|---|
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
SpringerOpen
2023-06-01
|
| Serie: | Insights into Imaging |
| Soggetti: | |
| Accesso online: | https://doi.org/10.1186/s13244-023-01439-0 |
| Tags: |
Nessun Tag, puoi essere il primo ad aggiungerne!!
|