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Data augmentation using generative adversarial networks (CycleGAN) to improve generalizability in CT segmentation tasks

Scientific reports, 2019-11, Vol.9 (1), p.16884-9, Article 16884

2019

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Progress in Fully Automated Abdominal CT Interpretation

American journal of roentgenology (1976), 2016-07, Vol.207 (1), p.67-79

Summers, Ronald M

2016

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Deep learning in medical imaging and radiation therapy

Medical physics (Lancaster), 2019-01, Vol.46 (1), p.e1-e36

2019

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Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning

IEEE transactions on medical imaging, 2016-05, Vol.35 (5), p.1285-1298

2016

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Opportunistic Osteoporosis Screening at Routine Abdominal and Thoracic CT: Normative L1 Trabecular Attenuation Values in More than 20 000 Adults

Radiology, 2019-05, Vol.291 (2), p.360-367

2019

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Automated Liver Fat Quantification at Nonenhanced Abdominal CT for Population-based Steatosis Assessment

Radiology, 2019-11, Vol.293 (2), p.334-342

2019

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Improving Computer-Aided Detection Using Convolutional Neural Networks and Random View Aggregation

IEEE transactions on medical imaging, 2016-05, Vol.35 (5), p.1170-1181

2016

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Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation

Medical image analysis, 2018-04, Vol.45, p.94-107

2018

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A Bottom-Up Approach for Pancreas Segmentation Using Cascaded Superpixels and (Deep) Image Patch Labeling

IEEE transactions on image processing, 2017-01, Vol.26 (1), p.386-399

2017

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A New 2.5D Representation for Lymph Node Detection Using Random Sets of Deep Convolutional Neural Network Observations

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014, 2014, Vol.17 (Pt 1), p.520-527

2014

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The future of digital health with federated learning

NPJ digital medicine, 2020-09, Vol.3 (1), p.119-119, Article 119

2020

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A Machine Learning Algorithm to Estimate Sarcopenia on Abdominal CT

Academic radiology, 2020-03, Vol.27 (3), p.311-320

2020

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Abdominal multi-organ segmentation from CT images using conditional shape–location and unsupervised intensity priors

Medical image analysis, 2015-12, Vol.26 (1), p.1-18

2015

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Automated CT biomarkers for opportunistic prediction of future cardiovascular events and mortality in an asymptomatic screening population: a retrospective cohort study

The Lancet. Digital health, 2020-04, Vol.2 (4), p.e192-e200

2020

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On the Interpretability of Artificial Intelligence in Radiology: Challenges and Opportunities

Radiology. Artificial intelligence, 2020-05, Vol.2 (3), p.e190043-e190043

2020

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Deep learning-based muscle segmentation and quantification at abdominal CT: application to a longitudinal adult screening cohort for sarcopenia assessment

British journal of radiology, 2019-08, Vol.92 (1100), p.20190327-20190327

2019

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Accuracy and agreement of PIRADSv2 for prostate cancer mpMRI: A multireader study

Journal of magnetic resonance imaging, 2017-02, Vol.45 (2), p.579-585

2017

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Fully Automated Abdominal CT Biomarkers for Type 2 Diabetes Using Deep Learning

Radiology, 2022-07, Vol.304 (1), p.85-95

2022

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Fully automated segmentation and quantification of visceral and subcutaneous fat at abdominal CT: application to a longitudinal adult screening cohort

British journal of radiology, 2018-09, Vol.91 (1089), p.20170968-20170968

2018

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Automated abnormality classification of chest radiographs using deep convolutional neural networks

NPJ digital medicine, 2020-05, Vol.3 (1), p.70-70, Article 70

2020

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Validation of the Dominant Sequence Paradigm and Role of Dynamic Contrast-enhanced Imaging in PI-RADS Version 2

Radiology, 2017-12, Vol.285 (3), p.859-869

2017

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Computer Aided-Diagnosis of Prostate Cancer on Multiparametric MRI: A Technical Review of Current Research

BioMed research international, 2014-01, Vol.2014 (2014), p.1-11

2014

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Polyp size measurement at CT colonography: what do we know and what do we need to know?

Radiology, 2010-06, Vol.255 (3), p.707-720

Summers, Ronald M

2010

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Fully Automated Deep Learning Tool for Sarcopenia Assessment on CT: L1 Versus L3 Vertebral Level Muscle Measurements for Opportunistic Prediction of Adverse Clinical Outcomes

American journal of roentgenology (1976), 2022-01, Vol.218 (1), p.124-131

2022

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Automated CT-Based Body Composition Analysis: A Golden Opportunity

Korean Journal of Radiology, 2021, 22(12), , pp.1934-1937

2021

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Data augmentation using generative adversarial networks (CycleGAN) to improve generalizability in CT segmentation tasks

Progress in Fully Automated Abdominal CT Interpretation

Deep learning in medical imaging and radiation therapy

Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning

Opportunistic Osteoporosis Screening at Routine Abdominal and Thoracic CT: Normative L1 Trabecular Attenuation Values in More than 20 000 Adults

Automated Liver Fat Quantification at Nonenhanced Abdominal CT for Population-based Steatosis Assessment

Improving Computer-Aided Detection Using Convolutional Neural Networks and Random View Aggregation

Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation

A Bottom-Up Approach for Pancreas Segmentation Using Cascaded Superpixels and (Deep) Image Patch Labeling

A New 2.5D Representation for Lymph Node Detection Using Random Sets of Deep Convolutional Neural Network Observations

The future of digital health with federated learning

A Machine Learning Algorithm to Estimate Sarcopenia on Abdominal CT

Abdominal multi-organ segmentation from CT images using conditional shape–location and unsupervised intensity priors

Automated CT biomarkers for opportunistic prediction of future cardiovascular events and mortality in an asymptomatic screening population: a retrospective cohort study

On the Interpretability of Artificial Intelligence in Radiology: Challenges and Opportunities

Deep learning-based muscle segmentation and quantification at abdominal CT: application to a longitudinal adult screening cohort for sarcopenia assessment

Accuracy and agreement of PIRADSv2 for prostate cancer mpMRI: A multireader study

Fully Automated Abdominal CT Biomarkers for Type 2 Diabetes Using Deep Learning

Fully automated segmentation and quantification of visceral and subcutaneous fat at abdominal CT: application to a longitudinal adult screening cohort

Automated abnormality classification of chest radiographs using deep convolutional neural networks

Validation of the Dominant Sequence Paradigm and Role of Dynamic Contrast-enhanced Imaging in PI-RADS Version 2

Computer Aided-Diagnosis of Prostate Cancer on Multiparametric MRI: A Technical Review of Current Research

Polyp size measurement at CT colonography: what do we know and what do we need to know?

Fully Automated Deep Learning Tool for Sarcopenia Assessment on CT: L1 Versus L3 Vertebral Level Muscle Measurements for Opportunistic Prediction of Adverse Clinical Outcomes

Automated CT-Based Body Composition Analysis: A Golden Opportunity

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