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
Colin JacobsRadboudumc, Nijmegen, The NetherlandsVerified email at radboudumc.nl
Pim de JongUMC UtrechtVerified email at umcutrecht.nl
Michael D. AbramoffProfessor of Ophthalmology and Visual Sciences, Electrical and Computer Engineering and Biomedical EngineeringVerified email at uiowa.edu
Eva van RikxoortCEO and Founder, ThironaVerified email at thirona.eu
Geert LitjensRadboud University Medical CenterVerified email at radboudumc.nl
Francesco CiompiRadboud University Medical Center, NijmegenVerified email at radboudumc.nl
Ivana IsgumProfessor of AI for Medical Image Analysis, Amsterdam University Medical CenterVerified email at amsterdamumc.nl
Jeroen van der LaakRadboud University Medical CenterVerified email at radboudumc.nl
Keelin MurphyAssistant Professor, Radboud University Medical CenterVerified email at radboudumc.nl
Arnaud Arindra Adiyoso SetioLunit Inc.Verified email at lunit.io
Nico KarssemeijerProfessor of Computer Aided Diagnosis, Radboud University NijmegenVerified email at radboudumc.nl
Marco LoogRadboud UniversityVerified email at ru.nl
Joes StaalStaff Algorithms Engineer at ArmVerified email at staalkemade.nl
Onno M MetsMD PhDVerified email at umcutrecht.nl
Mohsen GhafoorianSr. Staff Computer Vision R&D, QualcommVerified email at qti.qualcomm.com
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


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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	13495	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	4678	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	3235	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	2050	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	2023	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	1414	2016
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	1274	2023
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	1271	2009
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	1235	2017
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	1206	2016
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	1127	2017
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	1101	2019
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	1069	2004
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	1031	2020
The medical segmentation decathlon M Antonelli, A Reinke, S Bakas, K Farahani, A Kopp-Schneider, ... Nature communications 13 (1), 4128, 2022	1003	2022
A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises SK Zhou, H Greenspan, C Davatzikos, JS Duncan, B Van Ginneken, ... Proceedings of the IEEE 109 (5), 820-838, 2021	854	2021
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	834	2014
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	792	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	749	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	742	2001

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