Papers in international journals

  1. N.M. deSouza, E. Achten, A. Alberich-Bayarri, F. Bamberg, R. Boellaard, O. Clement, L. Fournier, F. Gallagher, X. Golay, C.P. Heussel, E.F. Jackson, R. Manniesing, M.E. Mayerhofer, E. Neri, J. O'Connor, K.K. Oguz, A. Persson, M. Smits, E.J.R. van Beek, C.J. Zech and E.S. of Radiology. "Validated imaging biomarkers as decision-making tools in clinical trials and routine practice: current status and recommendations from the EIBALL* subcommittee of the European Society of Radiology (ESR)", Insights into Imaging 2019;10:87. Abstract/PDF DOI PMID 31468205

  2. S.C. van de Leemput, M. Meijs, A. Patel, F. Meijer, B. van Ginneken and R. Manniesing. "Multiclass Brain Tissue Segmentation in 4D CT using Convolutional Neural Networks", IEEE Access 2019;7:51557-51569. Abstract/PDF DOI

  3. E. Abels, L. Pantanowitz, F. Aeffner, M.D. Zarella, J. van der Laak, M.M. Bui, V.N. Vemuri, A.V. Parwani, J. Gibbs, E. Agosto-Arroyo, A.H. Beck and C. Kozlowski. "Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the Digital Pathology Association", Journal of Pathology 2019;249:286-294. Abstract/PDF DOI PMID 31355445

  4. 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/PDF DOI PMID 30993030

  5. G. Aresta, C. Jacobs, T. Araujo, A. Cunha, I. Ramos, B. van Ginneken and A. Campilho. "iW-Net: an automatic and minimalistic interactive lung nodule segmentation deep network", Nature Scientific Reports 2019;9(11591). Abstract/PDF DOI PMID 31406194

  6. P. Bandi, M. Balkenhol, B. van Ginneken, J. van der Laak and G. Litjens. "Resolution-agnostic tissue segmentation in whole-slide histopathology images with convolutional neural networks", PeerJ 2019;7:e8242. Abstract/PDF DOI PMID 31871843

  7. M.F. Bakker, S.V. de Lange, R.M. Pijnappel, R.M. Mann, P.H.M. Peeters, E.M. Monninkhof, M.J. Emaus, C.E. Loo, R.H.C. Bisschops, M.B.I. Lobbes, M.D.F. de Jong, K.M. Duvivier, J. Veltman, N. Karssemeijer, H.J. de Koning, P.J. van Diest, W.P.T.M. Mali, M.A.A.J. van den Bosch, W.B. Veldhuis, C.H. van Gils and D.T.S. Group. "Supplemental MRI Screening for Women with Extremely Dense Breast Tissue", New England Journal of Medicine 2019;381:2091-2102. Abstract/PDF DOI PMID 31774954

  8. 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 2019;42:4555-4569. Abstract/PDF DOI PMID 30989469

  9. M.C.A. Balkenhol, D. Tellez, W. Vreuls, P.C. Clahsen, H. Pinckaers, F. Ciompi, P. Bult and J.A.W.M. van der Laak. "Deep learning assisted mitotic counting for breast cancer", Laboratory Investigation 2019. Abstract/PDF DOI PMID 31222166

  10. C. Balta, R.W. Bouwman, M.J. Broeders, N. Karssemeijer, W.J. Veldkamp, I. Sechopoulos and R.E. van Engen. "Optimization of the difference-of-Gaussian channel sets for the channelized Hotelling observer", Journal of Medical Imaging 2019;6(3):035501. Abstract/PDF DOI PMID 31572746

  11. 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 2019;46(2):124-129. Abstract/PDF DOI PMID 29625153

  12. J. Bleker, T. Kwee, R. Dierckx, I. de Jong, H. Huisman and D. Yakar. "Multiparametric MRI and auto-fixed volume of interest-based radiomics signature for clinically significant peripheral zone prostate cancer", European Radiology 2019. Abstract/PDF DOI PMID 31776744

  13. H. Bogunovic, F. Venhuizen, S. Klimscha, S. Apostolopoulos, A. Bab-Hadiashar, U. Bagci, M.F. Beg, L. Bekalo, Q. Chen, C. Ciller, K. Gopinath, A.K. Gostar, K. Jeon, Z. Ji, S.H. Kang, D.D. Koozekanani, D. Lu, D. Morley, K.K. Parhi, H.S. Park, A. Rashno, M. Sarunic, S. Shaikh, J. Sivaswamy, R. Tennakoon, S. Yadav, S. De Zanet, S.M. Waldstein, B.S. Gerendas, C. Klaver, C.I. Sanchez and U. Schmidt-Erfurth. "RETOUCH: The Retinal OCT Fluid Detection and Segmentation Benchmark and Challenge", IEEE Transactions on Medical Imaging 2019;38:1858-1874. Abstract/PDF DOI PMID 30835214

  14. J.-M. Bokhorst, A. Blank, A. Lugli, I. Zlobec, H. Dawson, M. Vieth, L.L. Rijstenberg, S. Brockmoeller, M. Urbanowicz, J.F. Flejou, R. Kirsch, F. Ciompi, J.A.W.M. van der Laak and I.D. Nagtegaal. "Assessment of individual tumor buds using keratin immunohistochemistry: moderate interobserver agreement suggests a role for machine learning", Modern Pathology 2019. Abstract/PDF DOI PMID 31844269

  15. W. Bulten, P. Bandi, 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

  16. 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

  17. 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

  18. M.U. Dalmis, 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;56:325-332. Abstract/PDF DOI PMID 30652985

  19. O.A. Debats, G.J.S. Litjens and H.J. Huisman. "Lymph node detection in MR Lymphography: false positive reduction using multi-view convolutional neural networks", PeerJ 2019;7:e8052. Abstract/PDF DOI PMID 31772836

  20. R.P. Finger, S. Schmitz-Valckenberg, M. Schmid, G.S. Rubin, H. Dunbar, A. Tufail, D.P. Crabb, A. Binns, C.I. Sanchez, P. Margaron, G. Normand, M.K. Durbin, U.F.O. Luhmann, P. Zamiri, J. Cunha-Vaz, F. Asmus, F.G. Holz and on behalf of the MACUSTAR consortium. "MACUSTAR: Development and Clinical Validation of Functional, Structural, and Patient-Reported Endpoints in Intermediate Age-Related Macular Degeneration", Ophthalmologica 2019;241:61-72. Abstract/PDF DOI PMID 30153664

  21. 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/PDF DOI PMID 30800522

  22. 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

  23. 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

  24. A. Halilovic, D.I. Verweij, A. Simons, M.J.P.L. Stevens-Kroef, S. Vermeulen, J. Elsink, B.B.J. Tops, I. Otte-Holler, J.A.W.M. van der Laak, C. van de Water, O.B.A. Boelens, M.S. Schlooz-Vries, J.R. Dijkstra, I.D. Nagtegaal, J. Tol, P.H.J. van Cleef, P.N. Span and P. Bult. "HER2, chromosome 17 polysomy and DNA ploidy status in breast cancer; a translational study", Scientific Reports 2019;9:11679. Abstract/PDF DOI PMID 31406196

  25. T.J. Heesterbeek, E.K. de Jong, I.E. Acar, J.M.M. Groenewoud, B. Liefers, C.I. Sanchez, 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

  26. A. Hering, S. Kuckertz, S. Heldmann and M.P. Heinrich. "Memory-efficient 2.5D convolutional transformer networks for multi-modal deformable registration with weak label supervision applied to whole-heart CT and MRI scans", Computer Assisted Radiology and Surgery 2019. Abstract/PDF DOI PMID 31538274

  27. M. Hermsen, T. de Bel, M. den Boer, E.J. Steenbergen, J. Kers, S. Florquin, J.J.T.H. Roelofs, M.D. Stegall, M.P. Alexander, B.H. Smith, B. Smeets, L.B. Hilbrands and J.A.W.M. van der Laak. "Deep-learning based histopathologic assessment of kidney tissue", Journal of the American Society of Nephrology 2019;30:1968-1979. Abstract/PDF DOI PMID 31488607

  28. 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

  29. H. Huisman. "Solid Science of AI Supporting Bladder Cancer CT Reading", Academic Radiology 2019;26(9):1146-1147. PDF DOI PMID 31324578

  30. C. Jacobs and B. van Ginneken. "Google's lung cancer AI: a promising tool that needs further validation", Nature Reviews Clinical Oncology 2019;16:532-533. Abstract/PDF DOI PMID 31249401

  31. N. Khalili, N. Lessmann, E. Turk, N.H. Claessens, R. de Heus, T. Kolk, M.A. Viergever, M.J. Benders and I. Išgum. "Automatic brain tissue segmentation in fetal MRI using convolutional neural networks", Magnetic Resonance Imaging 2019;64:77-89. DOI PMID 31181246

  32. J. van der Laak, F. Ciompi and G. Litjens. "No pixel-level annotations needed", Nature Biomedical Engineering 2019;3:855-856. PDF DOI PMID 31624355

  33. S.C. van de Leemput, J. Teuwen, B. van Ginneken and R. Manniesing. "MemCNN: A Python/PyTorch package for creating memory-efficient invertible neural networks", #JOSS# 2019;4(39):1576. Abstract/PDF DOI

  34. E.M. van Leijsen, M.I. Bergkamp, I.W. van Uden, S. Cooijmans, M. Ghafoorian, H.M. van der Holst, D.G. Norris, R.P. Kessels, B. Platel, A.M. Tuladhar and F.-E. de Leeuw. "Cognitive consequences of regression of cerebral small vessel disease", European Stroke Journal 2019;4:85-89. Abstract/PDF DOI PMID 31165098

  35. 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

  36. 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 2019;12:1808-1817. Abstract/PDF DOI PMID 30660540

  37. G. Litjens, F. Ciompi, J.M. Wolterink, B.D. de Vos, T. Leiner, J. Teuwen and I. Isgum. "State-of-the-Art Deep Learning in Cardiovascular Image Analysis", JACC Cardiovascular Imaging 2019;12:1549-1565. Abstract/PDF DOI PMID 31395244

  38. 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. Selnaes, G.M. Villeirs, J.J. Futterer 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/PDF DOI PMID 30946180

  39. M. Meijs, S.A. Pegge, K. Murayama, H.D. Boogaarts, M. Prokop, P.W. Willems, R. Manniesing and F.J. Meijer. "Color mapping of 4D-CTA for the detection of cranial arteriovenous shunts", American Journal of Neuroradiology 2019;40(9):1498-1504. Abstract/PDF DOI PMID 31395664

  40. M. Mullooly, B. Ehteshami Bejnordi, R.M. Pfeiffer, S. Fan, M. Palakal, M. Hada, P.M. Vacek, D.L. Weaver, J.A. Shepherd, B. Fan, A.P. Mahmoudzadeh, J. Wang, S. Malkov, J.M. Johnson, S.D. Herschorn, B.L. Sprague, S. Hewitt, L.A. Brinton, N. Karssemeijer, J. van der Laak, A. Beck, M.E. Sherman and G.L. Gierach. "Application of convolutional neural networks to breast biopsies to delineate tissue correlates of mammographic breast density", NPJ Breast Cancer 2019;5:43. Abstract/PDF DOI PMID 31754628

  41. I.D. Munsterman, M. Van Erp, G. Weijers, C. Bronkhorst, C.L. de Korte, J.P. Drenth, J.A. van der Laak and E.T. Tjwa. "A Novel Automatic Digital Algorithm that Accurately Quantifies Steatosis in NAFLD on Histopathological Whole-Slide Images", Cytometry Part B-Clinical Cytometry 2019. Abstract/PDF DOI PMID 31173462

  42. 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 2019;145:2954-2962. Abstract/PDF DOI PMID 30762225

  43. A. Patel, S.C. van de Leemput, M. Prokop, B. van Ginneken and R. Manniesing. "Image Level Training and Prediction: Intracranial Hemorrhage Identification in 3D Non-Contrast CT", IEEE Access 2019;7:92355-92364. Abstract/PDF DOI

  44. A. Patel, F.H.B.M. Schreuder, C.J.M. Klijn, M. Prokop, B. van Ginneken, H.A. Marquering, Y.B.W.E.M. Roos, M.I. Baharoglu, F.J.A. Meijer and R. Manniesing. "Intracerebral haemorrhage segmentation in non-contrast CT", Nature Scientific Reports 2019;9:17858. Abstract/PDF DOI PMID 31780815

  45. R.H.H.M. Philipsen, C.I. Sanchez, J. Melendez, W.J. Lew and B. van Ginneken. "Automated chest X-ray reading for tuberculosis in the Philippines to improve case detection: a cohort study", International Journal of Tuberculosis and Lung Disease 2019;23:805-810. Abstract/PDF DOI PMID 31439111

  46. 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

  47. A. Rodriguez-Ruiz, K. Lang, 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 2019;29:4825-4832. Abstract/PDF DOI PMID 30993432

  48. S. Saadatmand, H.A. Geuzinge, E.J.T. Rutgers, R.M. Mann, D.B.W. de Roy van Zuidewijn, H.M. Zonderland, R.A.E.M. Tollenaar, M.B.I. Lobbes, M.G.E.M. Ausems, M. van 't Riet, M.J. Hooning, I. Mares-Engelberts, E.J.T. Luiten, E.A.M. Heijnsdijk, C. Verhoef, N. Karssemeijer, J.C. Oosterwijk, I.-M. Obdeijn, H.J. de Koning, M.M.A. Tilanus-Linthorst and F. study group. "MRI versus mammography for breast cancer screening in women with familial risk (FaMRIsc): a multicentre, randomised, controlled trial", Lancet Oncology 2019;20:1136-1147. Abstract/PDF DOI PMID 31221620

  49. 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/PDF DOI PMID 31049740

  50. 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

  51. V. Schreur, A. de Breuk, F.G. Venhuizen, C.I. Sanchez, C.J. Tack, B.J. Klevering, E.K. de Jong and C.B. Hoyng. "Retinal hyperreflective foci in type 1 diabetes mellitus", Retina 2019. Abstract/PDF DOI PMID 31356496

  52. 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/PDF DOI PMID 29925511

  53. B. Sturm, D. Creytens, M.G. Cook, J. Smits, M.C.R.F. van Dijk, E. Eijken, E. Kurpershoek, H.V.N. Kusters-Vandevelde, A.H.A.G. Ooms, C. Wauters, W.A.M. Blokx and J.A.W.M. van der Laak. "Validation of Whole-slide Digitally Imaged Melanocytic Lesions: Does Z-Stack Scanning Improve Diagnostic Accuracy?", Journal of Pathology Informatics 2019;10:6. Abstract/PDF DOI PMID 30972225

  54. Z. Swiderska-Chadaj, H. Pinckaers, M. van Rijthoven, M. Balkenhol, M. Melnikova, O. Geessink, Q. Manson, M. Sherman, A. Polonia, J. Parry, M. Abubakar, G. Litjens, J. van der Laak and F. Ciompi. "Learning to detect lymphocytes in immunohistochemistry with deep learning", Medical Image Analysis 2019;58:101547. Abstract/PDF DOI PMID 31476576

  55. 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

  56. D. Tellez, G. Litjens, P. Bandi, W. Bulten, J.-M. Bokhorst, F. Ciompi and J. van der Laak. "Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology", Medical Image Analysis 2019;58:101544. Abstract/PDF DOI PMID 31466046

  57. D. Tellez, G. Litjens, J. van der Laak and F. Ciompi. "Neural Image Compression for Gigapixel Histopathology Image Analysis", IEEE Transactions on Pattern Analysis and Machine Intelligence 2019;58:101544. Abstract/PDF DOI PMID 31442971

  58. D. Valkenburg, E.H. Runhart, N.M. Bax, B. Liefers, S.L. Lambertus, C.I. Sanchez, F.P. Cremers and C.B. Hoyng. "Highly variable disease courses in siblings with Stargardt disease", Ophthalmology 2019;126:1712-1721. Abstract/PDF DOI PMID 31522899

  59. 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. Sjoblom, 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. M. Argus, C. Schaefer-Prokop, D.A. Lynch and B. van Ginneken. "Function Follows Form: Regression from Complete Thoracic Computed Tomography Scans", arXiv:1909.12047 2019. Abstract/PDF arXiv

  2. 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. Lipkova, 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. Hulsemeyer, M. Beetz, F. Ettlinger, F. Gruen, G. Kaissis, F. Lohofer, 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

  3. R. Dilz, L. Schröder, N. Moriakov, J.-J. Sonke and J. Teuwen. "Learned SIRT for Cone Beam Computed Tomography Reconstruction", arXiv:1908.10715 2019. Abstract

  4. C. Gonzalez-Gonzalo, B. Liefers, B. van Ginneken and C.I. Sanchez. "Iterative augmentation of visual evidence for weakly-supervised lesion localization in deep interpretability frameworks", arXiv:1910.07373 2019. Abstract

  5. S. Hu, D. Worrall, S. Knegt, B. Veeling, H. Huisman and M. Welling. "Supervised uncertainty quantification for segmentation with multiple annotations", arXiv:1907.01949 2019. Abstract

  6. B. Liefers, J.M. Colijn, C. Gonzalez-Gonzalo, T. Verzijden, P. Mitchell, C.B. Hoyng, B. van Ginneken, C.C. Klaver and C.I. Sanchez. "A deep learning model for segmentation of geographic atrophy to study its long-term natural history", arXiv:1908.05621 2019. Abstract arXiv

  7. L. Maier-Hein, A. Reinke, M. Kozubek, A.L. Martel, T. Arbel, M. Eisenmann, A. Hanbuary, P. Jannin, H. Muller, S. Onogur, J. Saez-Rodriguez, B. van Ginneken, A. Kopp-Schneider and B. Landman. "BIAS: Transparent reporting of biomedical image analysis challenges", arXiv:1910.04071 2019. Abstract/PDF arXiv

  8. 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 arXiv

  9. H. Pinckaers, B. van Ginneken and G. Litjens. "Streaming convolutional neural networks for end-to-end learning with multi-megapixel images", arXiv:1911.04432 2019. Abstract

  10. P. Putzky, D. Karkalousos, J. Teuwen, N. Moriakov, B. Bakker, M. Caan and M. Welling. "i-RIM applied to the fastMRI challenge", arXiv:1910.08952 2019. Abstract/PDF

  11. 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 arXiv

Papers in conference proceedings

  1. 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/PDF URL

  2. J.-M. Bokhorst, H. Pinckaers, P. van Zwam, I. Nagetgaal, J. van der Laak and F. Ciompi. "Learning from sparsely annotated data for semantic segmentation in histopathology images", in: Medical Imaging with Deep Learning, volume 102 of Proceedings of Machine Learning Research, 2019, pages 81-94. Abstract/PDF URL

  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 Proceedings of the SPIE, 2019. Abstract/PDF DOI

  4. E. Calli, K. Murphy, E. Sogancioglu 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. 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, page 1. Abstract/PDF DOI

  6. 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/PDF URL

  7. A. Hering, B. van Ginneken and S. Heldmann. "mlVIRNET: Multilevel Variational Image Registration Network", in: Medical Image Computing and Computer-Assisted Intervention, volume 11769 of Lecture Notes in Computer Science, 2019, pages 257-265. Abstract/PDF DOI arXiv

  8. A. Hering and S. Heldmann. "Unsupervised Learning for Large Motion Thoracic CT Follow-Up Registration", in: Medical Imaging, volume 10949 of Proceedings of the SPIE, 2019, page 109491B. Abstract/PDF DOI

  9. T.L.A. van den Heuvel, C.L. de Korte and B. van Ginneken. "Automated interpretation of prenatal ultrasound using a predefined acquisition protocol in resource-limited countries", in: Medical Imaging with Deep Learning, 2019. Abstract/PDF URL

  10. 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

  11. N. Lessmann, J.M. Wolterink, M. Zreik, M.A. Viergever, B. van Ginneken and I. Isgum. "Vertebra partitioning with thin-plate spline surfaces steered by a convolutional neural network", in: Medical Imaging with Deep Learning, 2019. Abstract/PDF arXiv

  12. B. Liefers, C. Gonzalez-Gonzalo, C. Klaver, B. van Ginneken and C.I. Sanchez. "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 URL

  13. H. Meine and A. Hering. "Efficient prealignment of CT scans for registration through a bodypart regressor", in: Medical Imaging with Deep Learning, 2019. Abstract/PDF URL

  14. C. Mercan, M. Balkenhol, J. van der Laak and F. Ciompi. "From Point Annotations to Epithelial Cell Detection in Breast Cancer Histopathology using RetinaNet", in: Medical Imaging with Deep Learning, 2019. Abstract/PDF URL

  15. 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 Proceedings of the SPIE, 2019. Abstract/PDF DOI arXiv

  16. T.F.A. van der Ouderaa, D.E. Worrall and B. van Ginneken. "Chest CT Super-resolution and Domain-adaptation using Memory-efficient 3D Reversible GANs", in: Medical Imaging with Deep Learning, 2019. Abstract/PDF URL

  17. 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, page 1. Abstract/PDF DOI

  18. D. Ruhe, V. Codreanu, C. van Leeuwen, D. Podareanu, V. Saletore and J. Teuwen. "Generating CT-scans with 3D Generative Adversarial Networks Using a Supercomputer", in: Medical Imaging meets NeurIPS, 2019. Abstract

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


  1. J.-M. Bokhorst, H. Dawson, A. Blank, I. Zlobec, A. Lugli, M. Vieth, R. Kirsch, M. Urbanowicz, S. Brockmoeller, J.-F. Flejou, L. Rijstenberg, J. van der Laak, F. Ciompi and I. Nagtegaal. "Assessment of tumor buds in colorectal cancer. A large-scale international digital observer study", in: European Congress of Pathology, 2019. Abstract

  2. 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

  3. G. Chlebus, G.E. Humpire Mamani, A. Schenk, B. van Ginneken and H. Meine. "Mimicking radiologists to improve the robustness of deep-learning based automatic liver segmentation", in: Annual Meeting of the Radiological Society of North America, 2019. Abstract

  4. J. Engelberts, C. Gonzalez-Gonzalo, C.I. Sanchez 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

  5. C. Gonzalez-Gonzalo, B. Liefers, A. Vaidyanathan, H. van Zeeland, C.C.W. Klaver and C.I. Sanchez. "Opening the "black box"? of deep learning in automated screening of eye diseases", in: Association for Research in Vision and Ophthalmology, 2019. Abstract URL

  6. D. Grob, L.J. Oostveen, C. Jacobs, M. Prokop, C. Schaefer-Prokop, I. Sechopoulos and M. Brink. "Intra-patient comparison of pulmonary nodule enhancement in subtraction CT and dual-energy CT", in: Annual Meeting of the European Society of Thoracic Imaging, 2019. Abstract

  7. 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

  8. C. Jacobs and B. van Ginneken. "Deep learning for detection and characterization of lung nodules", in: Annual Meeting of the European Society of Thoracic Imaging, 2019. Abstract

  9. C. Jacobs, E. Scholten, A. Schreuder, M. Prokop and B. van Ginneken. "An observer study comparing radiologists with the prize-winning lung cancer detection algorithms from the 2017 Kaggle Data Science Bowl", in: Annual Meeting of the Radiological Society of North America, 2019. Abstract

  10. B. Liefers, J. Colijn, C. Gonzalez-Gonzalo, A. Vaidyanathan, H. van Zeeland, P. Mitchell, C. Klaver and C.I. Sanchez. "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

  11. 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

  12. M. Silva, G. Milanese, F. Sabia, C. Jacobs, B. van Ginneken, M. Prokop, C. Schaefer-Prokop, A. Marchiano, N. Sverzellati and U. Pastorino. "Lung cancer risk after baseline round of screening: Only 20% of NLST eligibles require annual round", in: Annual Meeting of the European Society of Thoracic Imaging, 2019. Abstract

  13. M. Silva, G. Milanese, F. Sabia, C. Jacobs, B. van Ginneken, M. Prokop, C. Schaefer-Prokop, S. Sestini, A. Marchiano, N. Sverzellati and U. Pastorino. "Lung Cancer Screening in NLST Eligibles: Tailoring Annual Low-Dose Computed Tomography by Post-Test Risk Stratification", in: Annual Meeting of the Radiological Society of North America, 2019. Abstract

  14. D. Valkenburg, E. Runhart, B. Liefers, S. Lambertus, C.I. Sanchez, 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

  15. H. van Zeeland, J. Meakin, B. Liefers, C. Gonzalez-Gonzalo, A. Vaidyanathan, B. van Ginneken, C.C.W. Klaver and C.I. Sanchez. "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. C. Balta. "Objective image quality assessment in X-ray breast imaging", PhD thesis, Radboud University, Nijmegen, The Netherlands, 2019. Abstract/PDF

  2. M.U. Dalmis. "Automated Analysis of Breast MRI From traditional methods into deep learning", PhD thesis, Radboud University, Nijmegen, 2019. Abstract/PDF URL

  3. K. Dercksen. "Prostate Cancer Classification and Label Scarcity", Masters thesis, Radboud University, 2019. PDF

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

  5. D. Geijs. "Tumor segmentation in fluorescent TNBC immunohistochemical multiplex images using deep learning", Masters thesis, University of Twente, 2019. Abstract/PDF

  6. D. Grob. "Functional CT Imaging of the Lung: Substraction CT as a novel technique", PhD thesis, Radboud University, Nijmegen, The Netherlands, 2019. Abstract/PDF

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

  8. M. Kok. "Metastases Detection in Lymph Nodes using Transfer Learning", Masters thesis, Radboud University, 2019. Abstract/PDF

  9. N. Lessmann. "Machine Learning based quantification of extrapulmonary diseases in chest CT", PhD thesis, Utrecht University, 2019. Abstract/PDF URL

  10. 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

  11. R. Philipsen. "Automated chest radiography reading. Improvements, validation, and cost-effectiveness analysis", PhD thesis, Radboud University, Nijmegen, 2019. Abstract/PDF URL

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

  13. E. Smit. "Feasibility of a single-acquisition CT stroke protocol", PhD thesis, University of Utrecht, 2019. Abstract/PDF

  14. F. Venhuizen. "Machine Learning for Quantification of Age-Related Macular Degeneration Imaging Biomarkers in Optical Coherence Tomography", PhD thesis, Radboud University, Nijmegen, The Netherlands, 2019. Abstract/PDF

  15. J. Winkens. "Out-of-distribution detection for computational pathology with multi-head ensembles", Masters thesis, University of Amsterdam, 2019. Abstract/PDF

  16. J. van Zelst. "Automated 3D breast ultrasound Advances in breast cancer detection, diagnosis and screening", PhD thesis, Radboud University, Nijmegen, 2019. Abstract/PDF