Fully automatic deep learning in bi-institutional prostate magnetic resonance imaging: effects of cohort size and heterogeneity
N Netzer, C Weißer, P Schelb, X Wang, X Qin… - Investigative …, 2021 - journals.lww.com
Background The potential of deep learning to support radiologist prostate magnetic
resonance imaging (MRI) interpretation has been demonstrated. Purpose The aim of this …
resonance imaging (MRI) interpretation has been demonstrated. Purpose The aim of this …
[HTML][HTML] Application of a validated prostate MRI deep learning system to independent same-vendor multi-institutional data: demonstration of transferability
N Netzer, C Eith, O Bethge, T Hielscher, C Schwab… - European …, 2023 - Springer
Objectives To evaluate a fully automatic deep learning system to detect and segment
clinically significant prostate cancer (csPCa) on same-vendor prostate MRI from two different …
clinically significant prostate cancer (csPCa) on same-vendor prostate MRI from two different …
Classification of cancer at prostate MRI: deep learning versus clinical PI-RADS assessment
Background Men suspected of having clinically significant prostate cancer (sPC)
increasingly undergo prostate MRI. The potential of deep learning to provide diagnostic …
increasingly undergo prostate MRI. The potential of deep learning to provide diagnostic …
[HTML][HTML] Simulated clinical deployment of fully automatic deep learning for clinical prostate MRI assessment
P Schelb, X Wang, JP Radtke, M Wiesenfarth… - European …, 2021 - Springer
Objectives To simulate clinical deployment, evaluate performance, and establish quality
assurance of a deep learning algorithm (U-Net) for detection, localization, and segmentation …
assurance of a deep learning algorithm (U-Net) for detection, localization, and segmentation …
Performance of Deep Learning and Genitourinary Radiologists in Detection of Prostate Cancer Using 3‐T Multiparametric Magnetic Resonance Imaging
Background Several deep learning‐based techniques have been developed for prostate
cancer (PCa) detection using multiparametric magnetic resonance imaging (mpMRI), but …
cancer (PCa) detection using multiparametric magnetic resonance imaging (mpMRI), but …
A cascaded deep learning–based artificial intelligence algorithm for automated lesion detection and classification on biparametric prostate magnetic resonance …
Rationale and objectives Prostate MRI improves detection of clinically significant prostate
cancer; however, its diagnostic performance has wide variation. Artificial intelligence (AI) …
cancer; however, its diagnostic performance has wide variation. Artificial intelligence (AI) …
[HTML][HTML] Deep learning–assisted prostate cancer detection on bi-parametric MRI: minimum training data size requirements and effect of prior knowledge
M Hosseinzadeh, A Saha, P Brand, I Slootweg… - European …, 2022 - Springer
Abstract Objectives To assess Prostate Imaging Reporting and Data System (PI-RADS)–
trained deep learning (DL) algorithm performance and to investigate the effect of data size …
trained deep learning (DL) algorithm performance and to investigate the effect of data size …
[HTML][HTML] Anatomically guided self-adapting deep neural network for clinically significant prostate cancer detection on bi-parametric MRI: a multi-center study
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 …
scale bi-parametric MRI data, in detecting clinically significant prostate cancer (csPCa) in …
Bridging the gap between prostate radiology and pathology through machine learning
Background Prostate cancer remains the second deadliest cancer for American men despite
clinical advancements. Currently, magnetic resonance imaging (MRI) is considered the most …
clinical advancements. Currently, magnetic resonance imaging (MRI) is considered the most …
[HTML][HTML] Detecting prostate cancer with deep learning for MRI: a small step forward
AR Padhani, B Turkbey - Radiology, 2019 - pubs.rsna.org
Dr Baris Turkbey is an associate research physician at the Molecular Imaging Program,
National Cancer Institute, National Institutes of Health. He is a member of the International …
National Cancer Institute, National Institutes of Health. He is a member of the International …