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Automated Abdominal Segmentation of CT Scans for Body Composition Analysis Using Deep Learning

Radiology, 2019-03, Vol.290 (3), p.669

2019

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Residual Deep Convolutional Neural Network Predicts MGMT Methylation Status

Journal of digital imaging, 2017-10, Vol.30 (5), p.622-628

2017

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Radiomics-based Machine-learning Models Can Detect Pancreatic Cancer on Prediagnostic Computed Tomography Scans at a Substantial Lead Time Before Clinical Diagnosis

Gastroenterology (New York, N.Y. 1943), 2022-11, Vol.163 (5), p.1435-1446.e3

2022

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MRI texture features as biomarkers to predict MGMT methylation status in glioblastomas

Medical physics (Lancaster), 2016-06, Vol.43 (6), p.2835-2844

2016

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What Does Deep Learning See? Insights From a Classifier Trained to Predict Contrast Enhancement Phase From CT Images

American journal of roentgenology (1976), 2018-12, Vol.211 (6), p.1184

2018

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Development of a volumetric pancreas segmentation CT dataset for AI applications through trained technologists: a study during the COVID 19 containment phase

Abdominal radiology (New York), 2020-12, Vol.45 (12), p.4302-4310

2020

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S4 Intermuscular Adipose Tissue is Associated With the Severity of Acute Pancreatitis in Hospitalized Patients

The American journal of gastroenterology, 2023-10, Vol.118 (10S), p.S3-S5

2023

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S116 Association Between Body Composition Measured by Artificial Intelligence and the Long-Term Sequelae After Acute Pancreatitis

The American journal of gastroenterology, 2023-10, Vol.118 (10S), p.S92-S93

2023

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Performance of an Artificial Multi-observer Deep Neural Network for Fully Automated Segmentation of Polycystic Kidneys

Journal of digital imaging, 2017-08, Vol.30 (4), p.442-448

2017

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Acute Effect of Countermovement Jumping on Throwing Performance in Track and Field Athletes During Competition

Journal of strength and conditioning research, 2017-02, Vol.31 (2), p.359-364

2017

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Automated Segmentation of Hyperintense Regions in FLAIR MRI Using Deep Learning

Tomography (Ann Arbor), 2016-12, Vol.2 (4), p.334-340

2016

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Convolutional neural network for the detection of pancreatic cancer on CT scans

The Lancet. Digital health, 2020-09, Vol.2 (9), p.e453-e453

2020

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The basics of diffusion and perfusion imaging in brain tumors

Applied radiology (1976), 2014-07, Vol.43 (7), p.22-29

2014

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AI in the Loop: functionalizing fold performance disagreement to monitor automated medical image segmentation workflows

Frontiers in radiology, 2023, Vol.3, p.1223294-1223294

2023

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MIRMAID: A Content Management System for Medical Image Analysis Research

Radiographics, 2015-09, Vol.35 (5), p.1461

2015

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Deep Learning Improves the Temporal Reproducibility of Aortic Measurement

Journal of digital imaging, 2021-10, Vol.34 (5), p.1183-1189

2021

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Machine Learning for Medical Imaging

Radiographics, 2017-03, Vol.37 (2), p.505

2017

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Is There a Role for B-cell Depletion as Therapy for Scleroderma? A Case Report and Review of the Literature

Seminars in arthritis and rheumatism, 2010-10, Vol.40 (2), p.127-136

2010

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Toolkits and Libraries for Deep Learning

Journal of digital imaging, 2017-08, Vol.30 (4), p.400-405

2017

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Variability and accuracy of different software packages for dynamic susceptibility contrast magnetic resonance imaging for distinguishing glioblastoma progression from pseudoprogression

Journal of medical imaging (Bellingham, Wash.), 2015-04, Vol.2 (2), p.026001-026001

2015

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NIMG-26COMPARISON OF POST-GADOLINIUM 3D FAST SPIN ECHO IMAGES VERSUS REGISTERED AND SUBTRACTED MPRAGE IMAGES IN GLIOMA PATIENTS

Neuro-oncology (Charlottesville, Va.), 2015-11, Vol.17 (suppl 5), p.v159.2-v159

2015

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Deep Learning in Radiology: Does One Size Fit All?

Journal of the American College of Radiology, 2018-03, Vol.15 (3), p.521-526

2018

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Abstract PO-084: Automated detection of pancreatic ductal adenocarcinoma (PDAC) on CT scans using artificial intelligence (AI): Impact of inclusion of automated pancreas segmentation on the accuracy of 3D-convolutional neural network (CNN)

Clinical cancer research, 2021-03, Vol.27 (5_Supplement), p.PO-084-PO-084

2021

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Su1346: COMPUTED TOMOGRAPHY BASED RADIOMICS SIGNATURE: A POTENTIAL INDICATOR IN PRIMARY SCLEROSIS CHOLANGITIS USING THE BODY COMPOSITION MODEL

Gastroenterology (New York, N.Y. 1943), 2022-05, Vol.162 (7), p.S-1190

2022

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Automated Segmentation of Kidney Cortex and Medulla in CT Images: A Multisite Evaluation Study

Journal of the American Society of Nephrology, 2022-02, Vol.33 (2), p.420-430

2022

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Automated Abdominal Segmentation of CT Scans for Body Composition Analysis Using Deep Learning

Residual Deep Convolutional Neural Network Predicts MGMT Methylation Status

Radiomics-based Machine-learning Models Can Detect Pancreatic Cancer on Prediagnostic Computed Tomography Scans at a Substantial Lead Time Before Clinical Diagnosis

MRI texture features as biomarkers to predict MGMT methylation status in glioblastomas

What Does Deep Learning See? Insights From a Classifier Trained to Predict Contrast Enhancement Phase From CT Images

Development of a volumetric pancreas segmentation CT dataset for AI applications through trained technologists: a study during the COVID 19 containment phase

S4 Intermuscular Adipose Tissue is Associated With the Severity of Acute Pancreatitis in Hospitalized Patients

S116 Association Between Body Composition Measured by Artificial Intelligence and the Long-Term Sequelae After Acute Pancreatitis

Performance of an Artificial Multi-observer Deep Neural Network for Fully Automated Segmentation of Polycystic Kidneys

Acute Effect of Countermovement Jumping on Throwing Performance in Track and Field Athletes During Competition

Automated Segmentation of Hyperintense Regions in FLAIR MRI Using Deep Learning

Convolutional neural network for the detection of pancreatic cancer on CT scans

The basics of diffusion and perfusion imaging in brain tumors

AI in the Loop: functionalizing fold performance disagreement to monitor automated medical image segmentation workflows

MIRMAID: A Content Management System for Medical Image Analysis Research

Deep Learning Improves the Temporal Reproducibility of Aortic Measurement

Machine Learning for Medical Imaging

Is There a Role for B-cell Depletion as Therapy for Scleroderma? A Case Report and Review of the Literature

Toolkits and Libraries for Deep Learning

Variability and accuracy of different software packages for dynamic susceptibility contrast magnetic resonance imaging for distinguishing glioblastoma progression from pseudoprogression

NIMG-26COMPARISON OF POST-GADOLINIUM 3D FAST SPIN ECHO IMAGES VERSUS REGISTERED AND SUBTRACTED MPRAGE IMAGES IN GLIOMA PATIENTS

Deep Learning in Radiology: Does One Size Fit All?

Abstract PO-084: Automated detection of pancreatic ductal adenocarcinoma (PDAC) on CT scans using artificial intelligence (AI): Impact of inclusion of automated pancreas segmentation on the accuracy of 3D-convolutional neural network (CNN)

Su1346: COMPUTED TOMOGRAPHY BASED RADIOMICS SIGNATURE: A POTENTIAL INDICATOR IN PRIMARY SCLEROSIS CHOLANGITIS USING THE BODY COMPOSITION MODEL

Automated Segmentation of Kidney Cortex and Medulla in CT Images: A Multisite Evaluation Study

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