Bram van Ginneken

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Mathias ProkopProfessor of Radiology, RadboudumcVerified email at radboudumc.nl
Clara I. SánchezFull Professor, Informatics Institute, University of AmsterdamVerified email at uva.nl
Max ViergeverProfessor of Medical Imaging, University Medical Center UtrechtVerified email at isi.uu.nl
Pim de JongUMC UtrechtVerified email at umcutrecht.nl
Colin JacobsRadboudumc, Nijmegen, The NetherlandsVerified email at radboudumc.nl
Eva van RikxoortCEO and Founder, ThironaVerified email at thirona.eu
Michael D. AbramoffProfessor of Ophthalmology and Visual Sciences, Electrical and Computer Engineering and Biomedical EngineeringVerified email at uiowa.edu
Geert LitjensRadboud University Medical CenterVerified email at radboudumc.nl
Francesco CiompiRadboud University Medical Center, NijmegenVerified email at radboudumc.nl
Ivana IsgumUniversity Professor of AI and Medical Imaging, Amsterdam University Medical CenterVerified email at amsterdamumc.nl
Keelin MurphyAssistant Professor, Radboud University Medical CenterVerified email at radboudumc.nl
Jan-Willem LammersHoogleraar Longziekten UMC UtrechtVerified email at umcutrecht.nl
Jeroen van der LaakRadboud University Medical CenterVerified email at radboudumc.nl
Nico KarssemeijerProfessor of Computer Aided Diagnosis, Radboud University NijmegenVerified email at radboudumc.nl
Arnaud Arindra Adiyoso SetioSiemens HealthineersVerified email at siemens-healthineers.com
Marco LoogRadboud UniversityVerified email at ru.nl
Onno M MetsMD PhDVerified email at umcutrecht.nl
Joes StaalStaff Algorithms Engineer at ArmVerified email at staalkemade.nl
Laurens HogewegPhd Student, Radboud University Nijmegen Medical CentreVerified email at rad.umcn.nl
Josien PluimProfessor of Medical Image Analysis, Eindhoven University of Technology / UMC UtrechtVerified email at tue.nl

Bram van Ginneken

Professor of Medical Image Analysis, Radboud University

Verified email at radboudumc.nl - Homepage

Medical Image Analysis Medical Imaging Deep Learning Computer-Aided Diagnosis Machine Learning


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A survey on deep learning in medical image analysis G Litjens, T Kooi, BE Bejnordi, AAA Setio, F Ciompi, M Ghafoorian, ... Medical image analysis 42, 60-88, 2017	10887	2017
Ridge-based vessel segmentation in color images of the retina J Staal, MD Abràmoff, M Niemeijer, MA Viergever, B Van Ginneken IEEE transactions on medical imaging 23 (4), 501-509, 2004	4106	2004
Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer BE Bejnordi, M Veta, PJ Van Diest, B Van Ginneken, N Karssemeijer, ... Jama 318 (22), 2199-2210, 2017	2610	2017
Reflectance and texture of real-world surfaces KJ Dana, B Van Ginneken, SK Nayar, JJ Koenderink ACM Transactions On Graphics (TOG) 18 (1), 1-34, 1999	2005	1999
Guest editorial deep learning in medical imaging: Overview and future promise of an exciting new technique H Greenspan, B Van Ginneken, RM Summers IEEE transactions on medical imaging 35 (5), 1153-1159, 2016	1800	2016
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	1272	2016
Comparison and evaluation of methods for liver segmentation from CT datasets T Heimann, B Van Ginneken, MA Styner, Y Arzhaeva, V Aurich, C Bauer, ... IEEE transactions on medical imaging 28 (8), 1251-1265, 2009	1179	2009
Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis G Litjens, CI Sánchez, N Timofeeva, M Hermsen, I Nagtegaal, I Kovacs, ... Scientific reports 6 (1), 26286, 2016	1033	2016
Comparative study of retinal vessel segmentation methods on a new publicly available database M Niemeijer, J Staal, B Van Ginneken, M Loog, MD Abramoff Medical imaging 2004: image processing 5370, 648-656, 2004	1032	2004
Large scale deep learning for computer aided detection of mammographic lesions T Kooi, G Litjens, B Van Ginneken, A Gubern-Mérida, CI Sánchez, ... Medical image analysis 35, 303-312, 2017	994	2017
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	945	2017
CO-RADS: a categorical CT assessment scheme for patients suspected of having COVID-19—definition and evaluation M Prokop, W Van Everdingen, T van Rees Vellinga, H Quarles van Ufford, ... Radiology 296 (2), E97-E104, 2020	930	2020
A large annotated medical image dataset for the development and evaluation of segmentation algorithms AL Simpson, M Antonelli, S Bakas, M Bilello, K Farahani, B Van Ginneken, ... arXiv preprint arXiv:1902.09063, 2019	832	2019
The liver tumor segmentation benchmark (lits) P Bilic, P Christ, HB Li, E Vorontsov, A Ben-Cohen, G Kaissis, A Szeskin, ... Medical Image Analysis 84, 102680, 2023	798	2023
Computer analysis of computed tomography scans of the lung: a survey I Sluimer, A Schilham, M Prokop, B Van Ginneken IEEE transactions on medical imaging 25 (4), 385-405, 2006	762	2006
Active shape model segmentation with optimal features B Van Ginneken, AF Frangi, JJ Staal, BM ter Haar Romeny, MA Viergever Medical Imaging, IEEE Transactions on 21 (8), 924-933, 2002	745	2002
Computer-aided diagnosis in chest radiography: a survey B Van Ginneken, BMTH Romeny, MA Viergever IEEE Transactions on medical imaging 20 (12), 1228-1241, 2001	722	2001
Automatic detection of red lesions in digital color fundus photographs M Niemeijer, B Van Ginneken, J Staal, MSA Suttorp-Schulten, ... IEEE Transactions on medical imaging 24 (5), 584-592, 2005	682	2005
Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge G Litjens, R Toth, W Van De Ven, C Hoeks, S Kerkstra, B Van Ginneken, ... Medical image analysis 18 (2), 359-373, 2014	680	2014
Segmentation of anatomical structures in chest radiographs using supervised methods: a comparative study on a public database B Van Ginneken, MB Stegmann, M Loog Medical image analysis 10 (1), 19-40, 2006	632	2006

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