E. Scholten

发表

Risk‐based selection from the general population in a screening trial: Selection criteria, recruitment and power for the Dutch‐Belgian randomised lung cancer multi‐slice CT screening trial (NELSON)

J. Habbema, H. D. de Koning, K. Nackaerts, 2007, International journal of cancer.

Limited value of shape, margin and CT density in the discrimination between benign and malignant screen detected solid pulmonary nodules of the NELSON trial.

Harry J de Koning, Mathias Prokop, Rozemarijn Vliegenthart, 2008, European journal of radiology.

Automated Assessment of CO-RADS and Chest CT Severity Scores in Patients with Suspected COVID-19 Using Artificial Intelligence

Nikolas Lessmann, Luuk H Boulogne, Bram van Ginneken, 2020, Radiology.

Observer Variability for Classification of Pulmonary Nodules on Low-Dose CT Images and Its Effect on Nodule Management.

Bram van Ginneken, Colin Jacobs, Mathias Prokop, 2015, Radiology.

COVID-19 on Chest Radiographs: A Multireader Evaluation of an Artificial Intelligence System

Bram van Ginneken, Jaime Melendez, Keelin Murphy, 2020, Radiology.

Detection of lung cancer through low-dose CT screening (NELSON): a prespecified analysis of screening test performance and interval cancers.

H. D. de Koning, K. Nackaerts, C. Weenink, 2014, The Lancet. Oncology.

Characteristics of lung cancers detected by computer tomography screening in the randomized NELSON trial.

H. D. de Koning, K. Nackaerts, C. Weenink, 2013, American journal of respiratory and critical care medicine.

Corrigendum: Towards automatic pulmonary nodule management in lung cancer screening with deep learning

P. K. Gerke, B. van Ginneken, B. Ginneken, 2017, Scientific Reports.

Management of lung nodules detected by volume CT scanning.

Harry J de Koning, Mathias Prokop, Matthijs Oudkerk, 2009, The New England journal of medicine.

Smooth or attached solid indeterminate nodules detected at baseline CT screening in the NELSON study: cancer risk during 1 year of follow-up.

Ying Wang, Harry J de Koning, Mathias Prokop, 2009, Radiology.

Lung cancer probability in patients with CT-detected pulmonary nodules: a prespecified analysis of data from the NELSON trial of low-dose CT screening.

Harry J de Koning, Rozemarijn Vliegenthart, Matthijs Oudkerk, 2014, The Lancet. Oncology.

Solid, Part-Solid, or Non-Solid?: Classification of Pulmonary Nodules in Low-Dose Chest Computed Tomography by a Computer-Aided Diagnosis System

Bram van Ginneken, Colin Jacobs, Mathias Prokop, 2015, Investigative radiology.

Lung-RADS Category 4X: Does It Improve Prediction of Malignancy in Subsolid Nodules?

P. K. Gerke, B. van Ginneken, M. Prokop, 2017, Radiology.

Automated Estimation of Total Lung Volume using Chest Radiographs and Deep Learning pdf

Bram van Ginneken, Ecem Sogancioglu, Mathias Prokop, 2021, Medical physics.

Semi-Automatic Quantification of Subsolid Pulmonary Nodules: Comparison with Manual Measurements

B. van Ginneken, H. Gietema, H. D. de Koning, 2013, PloS one.

Towards a close computed tomography monitoring approach for screen detected subsolid pulmonary nodules?

B. van Ginneken, H. Gietema, H. D. de Koning, 2014, European Respiratory Journal.

Predictive Accuracy of the PanCan Lung Cancer Risk Prediction Model -External Validation based on CT from the Danish Lung Cancer Screening Trial

Colin Jacobs, Asger Dirksen, Jesper Holst Pedersen, 2015, European Radiology.

Detection and quantification of the solid component in pulmonary subsolid nodules by semiautomatic segmentation

B. Ginneken, H. Gietema, M. Prokop, 2015, European Radiology.

Artificial intelligence for detection and characterization of pulmonary nodules in lung cancer CT screening: ready for practice?

B. Ginneken, E. Scholten, C. Jacobs, 2020, Translational lung cancer research.

Computer aided detection of tuberculosis on chest radiographs: An evaluation of the CAD4TB v6 system

B. van Ginneken, K. Murphy, J. Melendez, 2019, Scientific Reports.

Computer aided detection of tuberculosis on chest radiographs: An evaluation of the CAD4TB v6 system

B. van Ginneken, K. Murphy, J. Melendez, 2019, Scientific Reports.

No benefit for consensus double reading at baseline screening for lung cancer with the use of semiautomated volumetry software.

H. D. de Koning, R. Vernhout, M. Oudkerk, 2012, Radiology.

Incidental perifissural nodules on routine chest computed tomography: lung cancer or not?

Bram van Ginneken, Wouter B. Veldhuis, Kaman Chung, 2017, European Radiology.

Pulmonary nodule enhancement in subtraction CT and dual-energy CT: A comparison study.

M. Prokop, I. Sechopoulos, C. Schaefer-Prokop, 2020, European journal of radiology.

Long-term effects of lung cancer computed tomography screening on health-related quality of life: the NELSON trial

H. D. de Koning, R. V. van Klaveren, M. Essink‐bot, 2010, European Respiratory Journal.

Baseline and second round results from the population based Dutch-Belgian randomized lung cancer screening trial (NELSON)

K. Nackaerts, M. Oudkerk, W. Mali, 2008 .

Volumetric computed tomography screening for lung cancer: three rounds of the NELSON trial

H. D. de Koning, K. Nackaerts, C. Weenink, 2013, European Respiratory Journal.

Computer aided detection of tuberculosis on chest radiographs: An evaluation of the CAD4TB v6 system

B. van Ginneken, K. Murphy, J. Melendez, 2019, Scientific Reports.

Explainable emphysema detection on chest radiographs with deep learning

B. van Ginneken, K. Murphy, E. Scholten, 2022, PloS one.

Deep Learning for Malignancy Risk Estimation of Pulmonary Nodules Detected at Low-Dose Screening CT.

Kiran Vaidhya Venkadesh, B. van Ginneken, M. Prokop, 2021, Radiology.

Development and Validation of a Convolutional Neural Network for Automated Detection of Scaphoid Fractures on Conventional Radiographs.

Bram van Ginneken, Steven Schalekamp, Eric Postma, 2021, Radiology. Artificial intelligence.

CT before and after ERCP: detection of pancreatic pseudotumor, asymptomatic retroperitoneal perforation, and duodenal diverticulum.

E. Scholten, G. L. Guit, L. Duijm, 1997, Gastrointestinal endoscopy.

Assisted versus Manual Interpretation of Low-Dose CT Scans for Lung Cancer Screening: Impact on Lung-RADS Agreement.

B. van Ginneken, M. Prokop, B. de Hoop, 2021, Radiology. Imaging cancer.

Malignancy risk estimation of screen-detected nodules at baseline CT: comparison of the PanCan model, Lung-RADS and NCCN guidelines

Bram van Ginneken, Colin Jacobs, Mathias Prokop, 2017, European Radiology.

Automatic detection of subsolid pulmonary nodules in thoracic computed tomography images

Bram van Ginneken, Jan-Martin Kuhnigk, Pim A. de Jong, 2014, Medical Image Anal..

Reduced Lung-Cancer Mortality with Volume CT Screening in a Randomized Trial.

Harry J de Koning, Mathias Prokop, Rozemarijn Vliegenthart, 2020, The New England journal of medicine.

Effect of nodule characteristics on variability of semiautomated volume measurements in pulmonary nodules detected in a lung cancer screening program.

Harry J de Koning, Mathias Prokop, Matthijs Oudkerk, 2008, Radiology.

Impact of computed tomography screening for lung cancer on participants in a randomized controlled trial (NELSON trial)

Harry J de Koning, Mathias Prokop, H. D. de Koning, 2008, Cancer.

Interscan variation of semi-automated volumetry of subsolid pulmonary nodules

B. Ginneken, H. Gietema, M. Prokop, 2014, European Radiology.

Classification of CT Pulmonary Opacities as Perifissural Nodules: Reader Variability.

B. van Ginneken, M. Prokop, C. Schaefer-Prokop, 2018, Radiology.

Handling label noise through model confidence and uncertainty: application to chest radiograph classification

Bram van Ginneken, Ecem Sogancioglu, Ernst Th. Scholten, 2019, Medical Imaging.

Deep Learning for Lung Cancer Detection in Screening CT Scans: Results of a Large-Scale Public Competition and an Observer Study with 11 Radiologists

P. K. Gerke, B. van Ginneken, P. Pinsky, 2021, Radiology: Artificial Intelligence.

Visual versus Automated Evaluation of Chest Computed Tomography for the Presence of Chronic Obstructive Pulmonary Disease

H. Gietema, M. Prokop, J. Lammers, 2012, PloS one.

Association between the number and size of intrapulmonary lymph nodes and chronic obstructive pulmonary disease severity

D. Lynch, B. van Ginneken, M. Prokop, 2020, PeerJ.

Subsolid pulmonary nodule morphology and associated patient characteristics in a routine clinical population

B. van Ginneken, C. Schaefer-Prokop, E. Scholten, 2016, European Radiology.

Computer-aided segmentation and volumetry of artificial ground-glass nodules at chest CT.

Jan-Martin Kuhnigk, Bram van Ginneken, Colin Jacobs, 2013, AJR. American journal of roentgenology.

University of Groningen Visual versus Automated Evaluation of Chest Computed Tomography for the Presence of Chronic Obstructive Pulmonary Disease Mets,

H. Gietema, M. Prokop, J. Lammers, 2012 .

Role of baseline nodule density and changes in density and nodule features in the discrimination between benign and malignant solid indeterminate pulmonary nodules.

Harry J de Koning, Mathias Prokop, Matthijs Oudkerk, 2009, European journal of radiology.

Typical CT Features of Intrapulmonary Lymph Nodes: A Review.

B. Ginneken, M. Prokop, C. Schaefer-Prokop, 2020, Radiology. Cardiothoracic imaging.

Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge

Hao Chen, Pheng-Ann Heng, Bram van Ginneken, 2016, Medical Image Anal..

Automatic classification of pulmonary peri-fissural nodules in computed tomography using an ensemble of 2D views and a convolutional neural network out-of-the-box

Bram van Ginneken, Pim A. de Jong, Mathias Prokop, 2015, Medical Image Anal..

Final screening round of the NELSON lung cancer screening trial: the effect of a 2.5-year screening interval

P. V. van Ooijen, H. D. de Koning, K. Nackaerts, 2016, Thorax.

Computed tomographic characteristics of interval and post screen carcinomas in lung cancer screening

M. Oudkerk, R. Vliegenthart, W. Mali, 2014, European Radiology.

Pulmonary nodules detected at lung cancer screening: interobserver variability of semiautomated volume measurements.

Mathias Prokop, Matthijs Oudkerk, Ying Wang, 2006, Radiology.

Lung cancer risk to personalise annual and biennial follow-up computed tomography screening

B. van Ginneken, M. Prokop, C. Schaefer-Prokop, 2018, Thorax.

Fully Automatic Volume Measurement of the Spleen at CT Using Deep Learning.

Bram van Ginneken, Colin Jacobs, Mathias Prokop, 2020, Radiology. Artificial intelligence.

Computer aided detection of tuberculosis on chest radiographs: An evaluation of the CAD4TB v6 system

B. van Ginneken, K. Murphy, J. Melendez, 2019, Scientific Reports.

Towards automatic pulmonary nodule management in lung cancer screening with deep learning

Bram van Ginneken, Paul K. Gerke, Colin Jacobs, 2016, Scientific Reports.

Observer variability for Lung-RADS categorisation of lung cancer screening CTs: impact on patient management

B. van Ginneken, M. Prokop, B. de Hoop, 2018, European Radiology.

Risk stratification based on screening history: the NELSON lung cancer screening study

H. D. de Koning, K. Nackaerts, H. Groen, 2017, Thorax.

Malignancy risk estimation of pulmonary nodules in screening CTs: Comparison between a computer model and human observers

Bram van Ginneken, Mathias Prokop, Asger Dirksen, 2017, PloS one.

Bag-of-Frequencies: A Descriptor of Pulmonary Nodules in Computed Tomography Images

Bram van Ginneken, Pim A. de Jong, Colin Jacobs, 2015, IEEE Transactions on Medical Imaging.

Automatic detection of spiculation of pulmonary nodules in computed tomography images

Bram van Ginneken, Colin Jacobs, Mathias Prokop, 2015, Medical Imaging.

Automatic segmentation of the solid core and enclosed vessels in subsolid pulmonary nodules

Eva M. van Rikxoort, Bram van Ginneken, Colin Jacobs, 2018, Scientific Reports.

Automatic Pulmonary Artery-Vein Separation and Classification in Computed Tomography Using Tree Partitioning and Peripheral Vessel Matching

Eva M. van Rikxoort, Jean-Paul Charbonnier, Monique Brink, 2016, IEEE Transactions on Medical Imaging.

THORACIC IMAGING : Predictive Nodule Characteristics at Follow-up

M. Prokop, M. Oudkerk, R. Vliegenthart, 2017 .

Visual discrimination of screen-detected persistent from transient subsolid nodules: An observer study

B. van Ginneken, M. Prokop, J. Goo, 2018, PloS one.

Malignancy estimation of Lung-RADS criteria for subsolid nodules on CT: accuracy of low and high risk spectrum when using NLST nodules

B. van Ginneken, M. Prokop, C. Schaefer-Prokop, 2017, European Radiology.

Trends in the incidence of pulmonary nodules in chest computed tomography: 10-year results from two Dutch hospitals.

B. van Ginneken, M. Prokop, C. Schaefer-Prokop, 2023, European radiology.

Management of lung nodules detected by volume CT scanning.

P. V. van Ooijen, H. Gietema, H. D. de Koning, 2009, The New England journal of medicine.

The Dutch-Belgian lung cancer screening trial (NELSON): Recruitment and baseline screening results

H. Gietema, K. Nackaerts, M. Prokop, 2006 .

Deep learning for the detection of benign and malignant pulmonary nodules in non-screening chest CT scans

B. van Ginneken, E. Scholten, C. Jacobs, 2023, Communications medicine.

Brock malignancy risk calculator for pulmonary nodules: validation outside a lung cancer screening population

P. K. Gerke, B. van Ginneken, M. Prokop, 2018, Thorax.

Automated Assessment of CO-RADS and Chest CT Severity Scores in Patients with Suspected COVID-19 Using Artificial Intelligence

P. K. Gerke, L. Beenen, H. Huisman, 2020, Radiology.

Short-term health-related quality of life consequences in a lung cancer CT screening trial (NELSON)

H. D. de Koning, M. Prokop, R. V. van Klaveren, 2009, British Journal of Cancer.

Nodule detection and generation on chest X-rays: NODE21 Challenge

K. Murphy, B. Ginneken, E. Scholten, 2024, IEEE transactions on medical imaging.

Automated estimation of total lung volume using chest radiographs and deep learning

K. Murphy, B. Ginneken, M. Prokop, 2021, Medical physics.

CT-Detected Subsolid Nodules: A Predictor of Lung Cancer Development at Another Location?

M. Prokop, C. Schaefer-Prokop, E. Scholten, 2021, Cancers.

THORACIC IMAGING : Predictive Nodule Characteristics at Follow-up

M. Prokop, M. Oudkerk, R. Vliegenthart, 2017 .