Publications by authors named "Patrick Schelb"

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Pseudoprospective Paraclinical Interaction of Radiology Residents With a Deep Learning System for Prostate Cancer Detection: Experience, Performance, and Identification of the Need for Intermittent Recalibration.
Kevin Sun Zhang, Patrick Schelb, Nils Netzer, Anoshirwan Andrej Tavakoli, Myriam Keymling

Invest Radiol· September 2022

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Fully Automatic Deep Learning in Bi-institutional Prostate Magnetic Resonance Imaging: Effects of Cohort Size and Heterogeneity.
Nils Netzer, Cedric Weißer, Patrick Schelb, Xianfeng Wang, Xiaoyan Qin

Invest Radiol· December 2021

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Improvement of PI-RADS-dependent prostate cancer classification by quantitative image assessment using radiomics or mean ADC.
Kevin Sun Zhang, Patrick Schelb, Simon Kohl, Jan Philipp Radtke, Manuel Wiesenfarth

Magn Reson Imaging· October 2021

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Comparison of Prostate MRI Lesion Segmentation Agreement Between Multiple Radiologists and a Fully Automatic Deep Learning System.
Patrick Schelb, Anoshirwan Andrej Tavakoli, Teeravut Tubtawee, Thomas Hielscher, Jan-Philipp Radtke

Rofo· May 2021

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Simulated clinical deployment of fully automatic deep learning for clinical prostate MRI assessment.
Patrick Schelb, Xianfeng Wang, Jan Philipp Radtke, Manuel Wiesenfarth, Philipp Kickingereder

Eur Radiol· January 2021

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Classification of Cancer at Prostate MRI: Deep Learning versus Clinical PI-RADS Assessment.
Patrick Schelb, Simon Kohl, Jan Philipp Radtke, Manuel Wiesenfarth, Philipp Kickingereder

Radiology· December 2019

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Histopathological to multiparametric MRI spatial mapping of extended systematic sextant and MR/TRUS-fusion-targeted biopsy of the prostate.
David Bonekamp, Patrick Schelb, Manuel Wiesenfarth, Tristan Anselm Kuder, Fenja Deister

Eur Radiol· April 2019

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Radiomic Machine Learning for Characterization of Prostate Lesions with MRI: Comparison to ADC Values.
David Bonekamp, Simon Kohl, Manuel Wiesenfarth, Patrick Schelb, Jan Philipp Radtke

Radiology· October 2018

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