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Deep learning in histopathology: the path to the clinic

Nature medicine, 2021-05, Vol.27 (5), p.775-784

2021

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Assessment of Prostate Cancer Aggressiveness Using Dynamic Contrast-enhanced Magnetic Resonance Imaging at 3 T

European urology, 2013-09, Vol.64 (3), p.448-455

2013

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Clinical evaluation of a computer-aided diagnosis system for determining cancer aggressiveness in prostate MRI

European radiology, 2015-11, Vol.25 (11), p.3187-3199

2015

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Automated deep-learning system for Gleason grading of prostate cancer using biopsies: a diagnostic study

The lancet oncology, 2020-02, Vol.21 (2), p.233-241

2020

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Lymph node detection in MR Lymphography: false positive reduction using multi-view convolutional neural networks

PeerJ (San Francisco, CA), 2019-11, Vol.7, p.e8052-e8052, Article e8052

2019

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State-of-the-Art Deep Learning in Cardiovascular Image Analysis

JACC. Cardiovascular imaging, 2019-08, Vol.12 (8), p.1549-1565

2019

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Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks

IEEE transactions on medical imaging, 2016-05, Vol.35 (5), p.1160-1169

2016

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The 2019 International Society of Urological Pathology (ISUP) Consensus Conference on Grading of Prostatic Carcinoma

The American journal of surgical pathology, 2020-08, Vol.44 (8), p.e87

2020

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Large scale deep learning for computer aided detection of mammographic lesions

Medical image analysis, 2017-01, Vol.35, p.303-312

2017

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Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis

Scientific reports, 2016-05, Vol.6 (1), p.26286-26286, Article 26286

2016

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Interpatient variation in normal peripheral zone apparent diffusion coefficient: effect on the prediction of prostate cancer aggressiveness

Radiology, 2012-10, Vol.265 (1), p.260

2012

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The Medical Segmentation Decathlon

Nature communications, 2022-07, Vol.13 (1), p.4128-4128, Article 4128

2022

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Multiparametric Magnetic Resonance Imaging for Discriminating Low-Grade From High-Grade Prostate Cancer

Investigative radiology, 2015-08, Vol.50 (8), p.490-497

2015

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Impact of rescanning and normalization on convolutional neural network performance in multi-center, whole-slide classification of prostate cancer

Scientific reports, 2020-09, Vol.10 (1), p.14398, Article 14398

2020

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A Single-Arm, Multicenter Validation Study of Prostate Cancer Localization and Aggressiveness With a Quantitative Multiparametric Magnetic Resonance Imaging Approach

Investigative radiology, 2019-07, Vol.54 (7), p.437

2019

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Stain Specific Standardization of Whole-Slide Histopathological Images

IEEE transactions on medical imaging, 2016-02, Vol.35 (2), p.404-415

2016

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Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities

Scientific reports, 2017-07, Vol.7 (1), p.5110-12, Article 5110

2017

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Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard

Scientific reports, 2019-01, Vol.9 (1), p.864-864, Article 864

2019

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Artificial intelligence assistance significantly improves Gleason grading of prostate biopsies by pathologists

Modern pathology, 2021-03, Vol.34 (3), p.660-671

2021

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Computer aided quantification of intratumoral stroma yields an independent prognosticator in rectal cancer

Cellular oncology (Dordrecht), 2019-06, Vol.42 (3), p.331-341

2019

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Computer-extracted Features Can Distinguish Noncancerous Confounding Disease from Prostatic Adenocarcinoma at Multiparametric MR Imaging

Radiology, 2016-01, Vol.278 (1), p.135

2016

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Differentiation of prostatitis and prostate cancer by using diffusion-weighted MR imaging and MR-guided biopsy at 3 T

Radiology, 2013-04, Vol.267 (1), p.164

2013

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Evaluation of prostate segmentation algorithms for MRI: The PROMISE12 challenge

Medical image analysis, 2014-02, Vol.18 (2), p.359-373

2014

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Deep learning in histopathology: the path to the clinic

Assessment of Prostate Cancer Aggressiveness Using Dynamic Contrast-enhanced Magnetic Resonance Imaging at 3 T

Clinical evaluation of a computer-aided diagnosis system for determining cancer aggressiveness in prostate MRI

Automated deep-learning system for Gleason grading of prostate cancer using biopsies: a diagnostic study

Lymph node detection in MR Lymphography: false positive reduction using multi-view convolutional neural networks

State-of-the-Art Deep Learning in Cardiovascular Image Analysis

Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks

The 2019 International Society of Urological Pathology (ISUP) Consensus Conference on Grading of Prostatic Carcinoma

Large scale deep learning for computer aided detection of mammographic lesions

Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis

Interpatient variation in normal peripheral zone apparent diffusion coefficient: effect on the prediction of prostate cancer aggressiveness

The Medical Segmentation Decathlon

Multiparametric Magnetic Resonance Imaging for Discriminating Low-Grade From High-Grade Prostate Cancer

Impact of rescanning and normalization on convolutional neural network performance in multi-center, whole-slide classification of prostate cancer

A Single-Arm, Multicenter Validation Study of Prostate Cancer Localization and Aggressiveness With a Quantitative Multiparametric Magnetic Resonance Imaging Approach

From Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 Challenge

Stain Specific Standardization of Whole-Slide Histopathological Images

Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge

Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities

Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard

Artificial intelligence assistance significantly improves Gleason grading of prostate biopsies by pathologists

Computer aided quantification of intratumoral stroma yields an independent prognosticator in rectal cancer

Computer-extracted Features Can Distinguish Noncancerous Confounding Disease from Prostatic Adenocarcinoma at Multiparametric MR Imaging

Differentiation of prostatitis and prostate cancer by using diffusion-weighted MR imaging and MR-guided biopsy at 3 T

Evaluation of prostate segmentation algorithms for MRI: The PROMISE12 challenge

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