Accepted or to appear

Papers in international journals

  1. N. Lessmann, P.A. de Jong, C. Celeng, R.A.P. Takx, M.A. Viergever, B. van Ginneken and I. Išgum. "Sex Differences in Coronary Artery and Thoracic Aorta Calcification and Their Association With Cardiovascular Mortality in Heavy Smokers", JACC Cardiovascular Imaging. Abstract/PDF DOI PMID 30660540

  2. R.J. Becks, R. Manniesing, J. Vister, S. Pegge, S.C. Steens, E.J. van Dijk, M. Prokop and F.J. Meijer. "Brain CT Perfusion Improves Intracranial Vessel Occlusion Detection on CT Angiography", Journal of Neuroradiology. Abstract/PDF DOI PMID 29625153

  3. G. Napolitano, E. Lynge, M. Lillholm, I. Vejborg, C.H. van Gils, M. Nielsen and N. Karssemeijer. "Change in mammographic density across birth cohorts of Dutch breast cancer screening participants", International Journal of Cancer. Abstract/PDF DOI PMID 30762225

  4. A. Rodriguez-Ruiz, K. Lång, A. Gubern-Merida, J. Teuwen, M. Broeders, G. Gennaro, P. Clauser, T.H. Helbich, M. Chevalier, T. Mertelmeier, M.G. Wallis, I. Andersson, S. Zackrisson, I. Sechopoulos and R.M. Mann. "Can we reduce the workload of mammographic screening by automatic identification of normal exams with artificial intelligence? A feasibility study", European Radiology. Abstract DOI PMID 30993432

Papers in conference proceedings

  1. J.-M. Bokhorst, H. Pinckaers, P. van Zwam, I. Nagtegaal, J. van der Laak and F. Ciompi. "Learning from sparsely annotated data for semantic segmentation in histopathology images", in: Medical Imaging with Deep Learning. Abstract/PDF


Papers in international journals

  1. A. Schreuder, C. Jacobs, L. Gallardo-Estrella, M. Prokop, C.M. Schaefer-Prokop and B. van Ginneken. "Predicting all-cause and lung cancer mortality using emphysema score progression rate between baseline and follow-up chest CT images: A comparison of risk model performances", PLoS One 2019;14:e0212756. Abstract/PDF DOI PMID 30789954

  2. N. Lessmann, B. van Ginneken, P.A. de Jong and I. Išgum. "Iterative fully convolutional neural networks for automatic vertebra segmentation and identification", Medical Image Analysis 2019;53:142-155. Abstract/PDF DOI arXiv PMID 30771712

  3. B. van Ginneken. "Deep Learning for Triage of Chest Radiographs: Should Every Institution Train Its Own System?", Radiology 2019;290:545-546. PDF DOI PMID 30422089

  4. M. Tammemagi, A.J. Ritchie, S. Atkar-Khattra, B. Dougherty, C. Sanghera, J.R. Mayo, R. Yuan, D. Manos, A.M. McWilliams, H. Schmidt, M. Gingras, S. Pasian, L. Stewart, S. Tsai, J.M.Seely, P. Burrowes, R. Bhatia, E.A.Haider, C. Boylan, C. Jacobs, B. van Ginneken, M.-S. Tsao, S. Lam and the Pan-Canadian Early Detection of Lung Cancer Study Group. "Predicting Malignancy Risk of Screen Detected Lung Nodules – Mean Diameter or Volume", Journal of Thoracic Oncology 2019;14:203-211. Abstract/PDF DOI PMID 30368011

  5. L. Aprupe, G. Litjens, T.J. Brinker, J. van der Laak and N. Grabe. "Robust and accurate quantification of biomarkers of immune cells in lung cancer micro-environment using deep convolutional neural networks.", PeerJ 2019;7:e6335. Abstract DOI PMID 30993030

  6. M.C.A. Balkenhol, P. Bult, D. Tellez, W. Vreuls, P.C. Clahsen, F. Ciompi and J.A.W.M. van der Laak. "Deep learning and manual assessment show that the absolute mitotic count does not contain prognostic information in triple negative breast cancer.", Cellular oncology (Dordrecht) 2019. Abstract DOI PMID 30989469

  7. S. Balocco, F. Ciompi, J. Rigla, X. Carrillo, J. Mauri and P. Radeva. "Assessment Of Intra-coronary Stent Location And Extension In Intravascular Ultrasound Sequences", Medical Physics 2019;46(2):484-493. Abstract/PDF DOI PMID 30383304

  8. W. Bulten, P. Bándi, J. Hoven, R. van de Loo, J. Lotz, N. Weiss, J. van der Laak, B. van Ginneken, C. Hulsbergen-van de Kaa and G. Litjens. "Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard", Nature Scientific Reports 2019;9(864). Abstract/PDF DOI arXiv PMID 30696866

  9. J.-P. Charbonnier, E. Pompe, C. Moore, S. Humphries, B. van Ginneken, B. Make, E. Regan, J.D. Crapo, E.M. van Rikxoort and D.A. Lynch. "Airway wall thickening on CT: Relation to smoking status and severity of COPD", Respiratory Medicine 2019;146:36-41. Abstract/PDF DOI PMID 30665516

  10. G. Chlebus, H. Meine, S. Thoduka, N. Abolmaali, B. van Ginneken, H.K. Hahn and A. Schenk. "Reducing inter-observer variability and interaction time of MR liver volumetry by combining automatic CNN-based liver segmentation and manual corrections", PLoS One 2019;14:e0217228. Abstract/PDF DOI PMID 31107915

  11. M.U. Dalmış, A. Gubern-Merida, S. Vreemann, P. Bult, N. Karssemeijer, R. Mann and J. Teuwen. "Artificial Intelligence Based Classification of Breast Lesions Imaged With a Multi-Parametric Breast MRI Protocol With ultrafast DCE-MRI, T2 and DWI", Investigative Radiology 2019. Abstract/PDF DOI PMID 30652985

  12. J.J. Gomez-Valverde, A. Anton, G. Fatti, B. Liefers, A. Herranz, A. Santos, C.I. Sanchez and M.J. Ledesma-Carbayo. "Automatic glaucoma classification using color fundus images based on convolutional neural networks and transfer learning", Biomedical Optics Express 2019;10(2):892-913. Abstract DOI

  13. O. Geessink, A. Baidoshvili, J. Klaase, B. Ehteshami Bejnordi, G. Litjens, G. van Pelt, W. Mesker, I. Nagtegaal, F. Ciompi and J. van der Laak. "Computer aided quantification of intratumoral stroma yields an independent prognosticator in rectal cancer", Cellular Oncology 2019:1-11. Abstract/PDF DOI PMID 30825182

  14. T.J. Heesterbeek, E.K. de Jong, I.E. Acar, J.M.M. Groenewoud, B. Liefers, C.I. Sánchez, T. Peto, C.B. Hoyng, D. Pauleikhoff, H.W. Hense and A.I. den Hollander. "Genetic risk score has added value over initial clinical grading stage in predicting disease progression in age-related macular degeneration", Nature Scientific Reports 2019;9:6611. Abstract/PDF DOI PMID 31036867

  15. T.L.A. van den Heuvel, H. Petros, S. Santini, C.L. de Korte and B. van Ginneken. "Automated Fetal Head Detection and Circumference Estimation from Free-Hand Ultrasound Sweeps Using Deep Learning in Resource-Limited Countries", Ultrasound in Medicine and Biology 2019;45(3):773-785. Abstract/PDF DOI PMID 30573305

  16. M.C. Maas, G.J.S. Litjens, A.J. Wright, U.I. Attenberger, M.A. Haider, T.H. Helbich, B. Kiefer, K.J. Macura, D.J.A. Margolis, A.R. Padhani, K.M. Selnæs, G.M. Villeirs, J.J. Fütterer and T.W.J. Scheenen. "A Single-Arm, Multicenter Validation Study of Prostate Cancer Localization and Aggressiveness With a Quantitative Multiparametric Magnetic Resonance Imaging Approach.", Investigative Radiology 2019. Abstract DOI PMID 30946180

  17. S.J. van Riel, C. Jacobs, E.T. Scholten, R. Wittenberg, M.M. Winkler Wille, B. de Hoop, R. Sprengers, O.M. Mets, B. Geurts, M. Prokop, C. Schaefer-Prokop and B. van Ginneken. "Observer variability for Lung-RADS categorisation of lung cancer screening CTs: impact on patient management", European Radiology 2019;29(2):924-931. Abstract/PDF DOI PMID 30066248

  18. W.B.G. Sanderink, B.I. Laarhuis, L.J.A. Strobbe, I. Sechopoulos, P. Bult, N. Karssemeijer and R.M. Mann. "A systematic review on the use of the breast lesion excision system in breast disease.", Insights into imaging 2019;10:49. Abstract DOI PMID 31049740

  19. V. Schreur, A. Domanian, B. Liefers, F.G. Venhuizen, B.J. Klevering, C.B. Hoyng, E.K. de Jong and T. Theelen. "Morphological and topographical appearance of microaneurysms on optical coherence tomography angiography", British Journal of Ophthalmology 2019;103(5):630-635. Abstract DOI PMID 29925511

  20. M. Veta, Y.J. Heng, N. Stathonikos, B.E. Bejnordi, F. Beca, T. Wollmann, K. Rohr, M.A. Shah, D. Wang, M. Rousson, M. Hedlund, D. Tellez, F. Ciompi, E. Zerhouni, D. Lanyi, M. Viana, V. Kovalev, V. Liauchuk, H.A. Phoulady, T. Qaiser, S. Graham, N. Rajpoot, E. Sjöblom, J. Molin, K. Paeng, S. Hwang, S. Park, Z. Jia, E.I.-C. Chang, Y. Xu, A.H. Beck, P.J. van Diest and J.P.W. Pluim. "Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge", Medical Image Analysis 2019;54(5):111-121. Abstract/PDF DOI PMID 30861443


  1. P. Bilic, P.F. Christ, E. Vorontsov, G. Chlebus, H. Chen, Q. Dou, C.-W. Fu, X. Han, P.-A. Heng, J. Hesser, S. Kadoury, T. Konopczynski, M. Le, C. Li, X. Li, J. Lipkovà, J. Lowengrub, H. Meine, J.H. Moltz, C. Pal, M. Piraud, X. Qi, J. Qi, M. Rempfler, K. Roth, A. Schenk, A. Sekuboyina, E. Vorontsov, P. Zhou, C. Hülsemeyer, M. Beetz, F. Ettlinger, F. Gruen, G. Kaissis, F. Lohöfer, R. Braren, J. Holch, F. Hofmann, W. Sommer, V. Heinemann, C. Jacobs, G.E. Humpire Mamani, B. van Ginneken, G. Chartrand, A. Tang, M. Drozdzal, A. Ben-Cohen, E. Klang, M.M. Amitai, E. Konen, H. Greenspan, J. Moreau, A. Hostettler, L. Soler, R. Vivanti, A. Szeskin, N. Lev-Cohain, J. Sosna, L. Joskowicz and B.H. Menze. "The Liver Tumor Segmentation Benchmark (LiTS)", arXiv:1901.04056 2019. Abstract

  2. C. González-Gonzalo, V. Sánchez-Gutiérrez, P. Hernández-Martínez, I. Contreras, Y.T. Lechanteur, A. Domanian, B. van Ginneken and C.I. Sánchez. "Evaluation of a deep learning system for the joint automated detection of diabetic retinopathy and age-related macular degeneration", arXiv:1903.09555 2019. Abstract

  3. K. Murphy, S.S. Habib, S.M.A. Zaidi, S. Khowaja, A. Khan, J. Melendez, E.T. Scholten, F. Amad, S. Schalekamp, M. Verhagen, R.H.H.M. Philipsen, A. Meijers and B. van Ginneken. "Computer aided detection of tuberculosis on chest radiographs: An evaluation of the CAD4TB v6 system", arXiv:1903.03349 2019. Abstract/PDF

  4. A.L. Simpson, M. Antonelli, S. Bakas, M. Bilello, K. Farahani, B. van Ginneken, A. Kopp-Schneider, B.A. Landman, G. Litjens, B. Menze, O. Ronneberger, R.M. Summers, P. Bilic, P.F. Christ, R.K.G. Do, M. Gollub, J. Golia-Pernicka, S.H. Heckers, W.R. Jarnagin, M.K. McHugo, S. Napel, E. Vorontsov, L. Maier-Hein and M.J. Cardoso. "A large annotated medical image dataset for the development and evaluation of segmentation algorithms", arXiv:1902.09063 2019. Abstract/PDF arXiv

Papers in conference proceedings

  1. E. Calli, E. Sogancioglu, E.T. Scholten, K. Murphy and B. van Ginneken. "Handling label noise through model confidence and uncertainty: application to chest radiograph classification", in: Medical Imaging of Proceedings of the SPIE, 2019. Abstract/PDF DOI

  2. T. de Bel, M. Hermsen, J. Kers, J. van der Laak and G. Litjens. "Stain-Transforming Cycle-Consistent Generative Adversarial Networks for Improved Segmentation of Renal Histopathology", in: Medical Imaging with Deep Learning, 2019. Abstract arXiv

  3. M. Caballo, J. Teuwen, R. Mann and I. Sechopolous. "Breast parenchyma analysis and classification for breast masses detection using texture feature descriptors and neural networks in dedicated breast CT images", in: Medical Imaging of SPIE, 2019. Abstract/PDF DOI

  4. E. Calli, K. Murphy, E. Sogancioglu, E.T. Scholten and B. van Ginneken. "FRODO: Free rejection of out-of-distribution samples: application to chest x-ray analysis", in: Medical Imaging with Deep Learning, 2019. Abstract/PDF URL

  5. M. Hosseinzadeh, P. Brand and H. Huisman. "Effect of Adding Probabilistic Zonal Prior in Deep Learning-based Prostate Cancer Detection", in: Medical Imaging with Deep Learning, 2019. Abstract/PDF URL

  6. B. Liefers, C. González-Gonzalo, C. Klaver, B. van Ginneken and C.I. Sánchez. "Dense Segmentation in Selected Dimensions: Application to Retinal Optical Coherence Tomography", in: Medical Imaging with Deep Learning, volume 102 of Proceedings of Machine Learning Research, 2019, pages 337-346. Abstract/PDF

  7. N. Moriakov, K. Michielsen, R. Mann, J. Adler, I. Sechopolous and J. Teuwen. "Deep learning framework for digital breast tomosynthesis reconstruction", in: Medical Imaging of SPIE, 2019. Abstract/PDF arXiv

  8. H. Pinckaers, W. Bulten and G. Litjens. "High resolution whole prostate biopsy classification using streaming stochastic gradient descent", in: Medical Imaging of Proceedings of the SPIE, 2019. Abstract/PDF DOI

  9. J. van Vugt, E. Marchiori, R. Mann, A. Gubern-Mérida, N. Moriakov and J. Teuwen. "Vendor-independent soft tissue lesion detection using weakly supervised and unsupervised adversarial domain adaptation", in: Medical Imaging of SPIE, 2019. Abstract/PDF DOI


  1. W. Bulten, H. Pinckaers, C. Hulsbergen-van de Kaa and G. Litjens. "Automated Gleason Grading of Prostate Biopsies Using Deep Learning", in: United States and Canadian Academy of Pathology (USCAP) 108th Annual Meeting, 2019. Abstract

  2. K. Dercksen, W. Bulten and G. Litjens. "Dealing with Label Scarcity in Computational Pathology: A Use Case in Prostate Cancer Classification", in: Medical Imaging with Deep Learning, 2019. Abstract arXiv

  3. J. Engelberts, C. González-Gonzalo, C.I. Sánchez and M.J. van Grinsven. "Automatic Segmentation of Drusen and Exudates on Color Fundus Images using Generative Adversarial Networks", in: Association for Research in Vision and Ophthalmology, 2019. Abstract

  4. C. González-Gonzalo, B. Liefers, A. Vaidyanathan, H. van Zeeland, C.C.W. Klaver and C.I. Sánchez. "Opening the “black box” of deep learning in automated screening of eye diseases", in: Association for Research in Vision and Ophthalmology, 2019. Abstract

  5. T.L.A. van den Heuvel, B. van Ginneken and C.L. de Korte. "Improving Maternal Care In Resource-Limited Settings Using A Low-Cost Ultrasound Device And Machine Learning", in: Dutch Bio-Medical Engineering Conference, 2019. Abstract/PDF

  6. B. Liefers, J. Colijn, C. González-Gonzalo, A. Vaidyanathan, H. van Zeeland, P. Mitchell, C. Klaver and C.I. Sánchez. "Prediction of areas at risk of developing geographic atrophy in color fundus images using deep learning", in: Association for Research in Vision and Ophthalmology, 2019. Abstract

  7. W. Sanderink, J. Teuwen, L. Appelman, I. Sechopoulos, N. Karssemeijer and R. Mann. "Simultaneous multi-slice single-shot DWI compared to routine read-out-segmented DWI for evaluation of breast lesions", in: Annual Meeting of the International Society for Magnetic Resonance in Medicine, 2019. Abstract

  8. D. Valkenburg, E. Runhart, B. Liefers, S. Lambertus, C.I. Sánchez, F.P. Cremers, B. Nathalie M and C.C.B. Hoyng. "Familial discordance in disease phenotype in siblings with Stargardt disease", in: Association for Research in Vision and Ophthalmology, 2019. Abstract

  9. H. van Zeeland, J. Meakin, B. Liefers, C. González-Gonzalo, A. Vaidyanathan, B. van Ginneken, C.C.W. Klaver and C.I. Sánchez. "EyeNED workstation: Development of a multi-modal vendor-independent application for annotation, spatial alignment and analysis of retinal images", in: Association for Research in Vision and Ophthalmology, 2019. Abstract


  1. T. van der Ouderaa. "Reversible Networks for Memory-efficient Image-to-Image Translation in 3D Medical Imaging", Masters thesis, University of Amsterdam, 2019. Abstract/PDF

  2. L.G. Estrella. "Quantification of COPD biomarkers in thoracic CT scans", PhD thesis, Radboud University, Nijmegen, The Netherlands, 2019. Abstract/PDF

  3. T.L.A. van den Heuvel. "Automated low-cost ultrasound: improving antenatal care in resource-limited settings", PhD thesis, Radboud University, Nijmegen, The Netherlands, 2019. Abstract/PDF

  4. N. Lessmann. "Machine Learning based quantification of extrapulmonary diseases in chest CT", PhD thesis, 2019. Abstract URL

  5. R. Philipsen. "Automated chest radiography reading. Improvements, validation, and cost-effectiveness analysis.", PhD thesis, 2019. Abstract/PDF

  6. A.R. Ruiz. "Artificial intelligence & tomosynthesis for breast cancer detection", PhD thesis, Radboud University, Nijmegen, The Netherlands, 2019. Abstract/PDF