Cikkek nyilvánosan hozzáférhető megbízással - Colin JacobsTovábbi információ
Valahol hozzáférhető: 37
Pulmonary nodule detection in ct images: false positive reduction using multi-view convolutional networks
AAA Setio, F Ciompi, G Litjens, P Gerke, C Jacobs, SJ van Riel, ...
IEEE transactions on medical imaging 35 (5), 1160-1169, 2016
Megbízások: Netherlands Organisation for Scientific Research
Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the LUNA16 challenge
AAA Setio, A Traverso, T De Bel, MSN Berens, C van den Bogaard, ...
Medical image analysis 42, 1-13, 2017
Megbízások: Research Foundation (Flanders), Netherlands Organisation for Scientific Research
Towards automatic pulmonary nodule management in lung cancer screening with deep learning
F Ciompi, K Chung, SJ van Riel, AAA Setio, PK Gerke, C Jacobs, ...
Scientific Reports 7, 2017
Megbízások: Netherlands Organisation for Scientific Research, Government of Italy
Towards a close computed tomography monitoring approach for screen detected subsolid pulmonary nodules?
ET Scholten, PA de Jong, B de Hoop, R van Klaveren, ...
European Respiratory Journal 45 (3), 765-773, 2015
Megbízások: Dutch Cancer Society
Relational modeling for robust and efficient pulmonary lobe segmentation in ct scans
W Xie, C Jacobs, JP Charbonnier, B van Ginneken
IEEE transactions on medical imaging 39 (8), 2664-2675, 2020
Megbízások: US National Institutes of Health
Deep Learning for Malignancy Risk Estimation of Pulmonary Nodules Detected at Low-Dose Screening CT
KV Venkadesh, AAA Setio, A Schreuder, ET Scholten, K Chung, ...
Radiology 300 (2), 438-447, 2021
Megbízások: Netherlands Organisation for Scientific Research
iW-Net: an automatic and minimalistic interactive lung nodule segmentation deep network
G Aresta, C Jacobs, T Araújo, A Cunha, I Ramos, B van Ginneken, ...
Scientific reports 9 (1), 1-9, 2019
Megbízások: Fundação para a Ciência e a Tecnologia, Portugal
Robust semi-automatic segmentation of pulmonary subsolid nodules in chest computed tomography scans
BC Lassen, C Jacobs, JM Kuhnigk, B van Ginneken, EM van Rikxoort
Physics in Medicine & Biology 60 (3), 1307, 2015
Megbízások: US National Institutes of Health
Predictive Accuracy of the PanCan Lung Cancer Risk Prediction Model-External Validation based on CT from the Danish Lung Cancer Screening Trial
MMW Wille, SJ van Riel, Z Saghir, A Dirksen, JH Pedersen, C Jacobs, ...
European radiology 25 (10), 3093-3099, 2015
Megbízások: Fraunhofer-Gesellschaft
Long-Term Active Surveillance of Screening Detected Subsolid Nodules is a Safe Strategy to Reduce Overtreatment
M Silva, M Prokop, C Jacobs, G Capretti, N Sverzellati, F Ciompi, ...
Journal of Thoracic Oncology 13 (10), 1454-1463, 2018
Megbízások: Fondazione Cariplo, Government of Italy
Detection and quantification of the solid component in pulmonary subsolid nodules by semiautomatic segmentation
ET Scholten, C Jacobs, B van Ginneken, S van Riel, R Vliegenthart, ...
European radiology 25 (2), 488-496, 2015
Megbízások: Dutch Cancer Society
Lung-RADS category 4X: does it improve prediction of malignancy in subsolid nodules?
K Chung, C Jacobs, ET Scholten, JM Goo, H Prosch, N Sverzellati, ...
Radiology 284 (1), 264-271, 2017
Megbízások: Dutch Cancer Society
Observer variability for Lung-RADS categorisation of lung cancer screening CTs: impact on patient management
SJ van Riel, C Jacobs, ET Scholten, R Wittenberg, MM Winkler Wille, ...
European radiology 29 (2), 924-931, 2019
Megbízások: US National Institutes of Health
Detection of Subsolid Nodules in Lung Cancer Screening: Complementary Sensitivity of Visual Reading and Computer-Aided Diagnosis
M Silva, CM Schaefer-Prokop, C Jacobs, G Capretti, F Ciompi, ...
Investigative radiology 53 (8), 441-449, 2018
Megbízások: Fondazione Cariplo, Government of Italy
Brock malignancy risk calculator for pulmonary nodules: validation outside a lung cancer screening population
K Chung, OM Mets, PK Gerke, C Jacobs, AM den Harder, ET Scholten, ...
Thorax 73 (9), 857-863, 2018
Megbízások: Dutch Cancer Society
Classification of CT pulmonary opacities as perifissural nodules: reader variability
A Schreuder, B van Ginneken, ET Scholten, C Jacobs, M Prokop, ...
Radiology 288 (3), 867-875, 2018
Megbízások: Dutch Cancer Society
Lung cancer screening by nodule volume in Lung-RADS v1. 1: negative baseline CT yields potential for increased screening interval
M Silva, G Milanese, S Sestini, F Sabia, C Jacobs, B van Ginneken, ...
European radiology 31 (4), 1956-1968, 2021
Megbízások: Fondazione Cariplo, Government of Italy, AIRC Foundation for Cancer Research …
Fully Automatic Volume Measurement of the Spleen at CT Using Deep Learning
GE Humpire-Mamani, J Bukala, ET Scholten, M Prokop, B van Ginneken, ...
Radiology: Artificial Intelligence 2 (4), e190102, 2020
Megbízások: Fraunhofer-Gesellschaft
Semi-automatic quantification of subsolid pulmonary nodules: comparison with manual measurements
ET Scholten, B de Hoop, C Jacobs, S van Amelsvoort-van de Vorst, ...
PLoS One 8 (11), e80249, 2013
Megbízások: Dutch Cancer Society
Interscan variation of semi-automated volumetry of subsolid pulmonary nodules
ET Scholten, PA de Jong, C Jacobs, B van Ginneken, S van Riel, ...
European Radiology 25 (4), 1040-1047, 2015
Megbízások: Fraunhofer-Gesellschaft, Dutch Cancer Society
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