Papers in international journals

  1. M. Silva, G. Milanese, S. Sestini, F. Sabia, C. Jacobs, B. van Ginneken, M. Prokop, C. Schaefer-Prokop, A. Marchiano, N. Sverzellati and U. Pastorino, "Lung cancer screening by nodule volume in Lung-RADS v1.1: negative baseline CT yields potential for increased screening interval", European Radiology, 2020. Abstract/PDF DOI PMID
  2. M. Hermsen, B. Smeets, L. Hilbrands and J. van der Laak, "Artificial intelligence; is there a potential role in nephropathology?", Nephrology Dialysis Transplantation, 2020. Abstract/PDF DOI PMID
  3. T. Kootstra, J. Teuwen, J. Goudsmit, T. Nijboer, M. Dodd and S. Van der Stigchel, "Machine learning-based classification of viewing behavior using a wide range of statistical oculomotor features", Journal of Vision, 2020;20(9):1. Abstract/PDF DOI PMID
  4. Z. Swiderska-Chadaj, T. de Bel, L. Blanchet, A. Baidoshvili, D. Vossen, J. van der Laak and G. Litjens, "Impact of rescanning and normalization on convolutional neural network performance in multi-center, whole-slide classification of prostate cancer", Scientific Reports, 2020;10(1):14398. Abstract/PDF DOI PMID
  5. H. Pinckaers, B. van Ginneken and G. Litjens, "Streaming convolutional neural networks for end-to-end learning with multi-megapixel images", IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020. Abstract/PDF DOI PMID
  6. S. Schalekamp, M. Huisman, R. van Dijk, M. Boomsma, P. Freire Jorge, W. de Boer, G. Herder, M. Bonarius, O. Groot, E. Jong, A. Schreuder and C. Schaefer-Prokop, "Model-based Prediction of Critical Illness in Hospitalized Patients with COVID-19", Radiology, 2020:202723. Abstract/PDF DOI PMID
  7. W. Bulten, M. Balkenhol, J. Belinga, A. Brilhante, A. Çakır, L. Egevad, M. Eklund, X. Farré, K. Geronatsiou, V. Molinié, G. Pereira, P. Roy, G. Saile, P. Salles, E. Schaafsma, J. Tschui, A. Vos, B. Delahunt, H. Samaratunga, D. Grignon, A. Evans, D. Berney, C. Pan, G. Kristiansen, J. Kench, J. Oxley, K. Leite, J. McKenney, P. Humphrey, S. Fine, T. Tsuzuki, M. Varma, M. Zhou, E. Comperat, D. Bostwick, K. Iczkowski, C. Magi-Galluzzi, J. Srigley, H. Takahashi, T. van der Kwast, H. van Boven, R. Vink, J. van der Laak, C. der Hulsbergen-van Kaa and G. Litjens, "Artificial Intelligence Assistance Significantly Improves Gleason Grading of Prostate Biopsies by Pathologists", Modern Pathology, 2020. Abstract/PDF DOI PMID
  8. C. González-Gonzalo, B. Liefers, B. van Ginneken and C. Sánchez, "Iterative augmentation of visual evidence for weakly-supervised lesion localization in deep interpretability frameworks: application to color fundus images", IEEE Transactions on Medical Imaging, 2020. Abstract/PDF DOI PMID
  9. W. Xie, C. Jacobs, J. Charbonnier and B. van Ginneken, "Relational Modeling for Robust and Efficient Pulmonary Lobe Segmentation in CT Scans", IEEE Transactions on Medical Imaging, 2020;39(8):2664-2675. Abstract/PDF DOI PMID Cited by ~5 Algorithm
  10. N. Lessmann, C. Sánchez, L. Beenen, L. Boulogne, M. Brink, E. Calli, J. Charbonnier, T. Dofferhoff, W. van Everdingen, P. Gerke, B. Geurts, H. Gietema, M. Groeneveld, L. van Harten, N. Hendrix, W. Hendrix, H. Huisman, I. Isgum, C. Jacobs, R. Kluge, M. Kok, J. Krdzalic, B. Lassen-Schmidt, K. van Leeuwen, J. Meakin, M. Overkamp, T. van Rees Vellinga, E. van Rikxoort, R. Samperna, C. Schaefer-Prokop, S. Schalekamp, E. Scholten, C. Sital, L. Stöger, J. Teuwen, K. Vaidhya Venkadesh, C. de Vente, M. Vermaat, W. Xie, B. de Wilde, M. Prokop and B. van Ginneken, "Automated Assessment of CO-RADS and Chest CT Severity Scores in Patients with Suspected COVID-19 Using Artificial Intelligence", Radiology, 2020. Abstract/PDF DOI PMID Algorithm
  11. A. Schreuder, C. Jacobs, E. Scholten, M. Prokop, B. van Ginneken, D. Lynch and C. Schaefer-Prokop, "Association between the number and size of intrapulmonary lymph nodes and chronic obstructive pulmonary disease severity", PeerJ, 2020;8:e9166. Abstract/PDF DOI PMID
  12. I. Sechopoulos, J. Teuwen and R. Mann, "Artificial Intelligence for Breast Cancer Detection in Mammography: state of the art", Seminars in Cancer Biology, 2020. Abstract/PDF DOI PMID
  13. G. van Leenders, T. van der Kwast, D. Grignon, A. Evans, G. Kristiansen, C. Kweldam, G. Litjens, J. McKenney, J. Melamed, N. Mottet, G. Paner, H. Samaratunga, I. Schoots, J. Simko, T. Tsuzuki, M. Varma, A. Warren, T. Wheeler, S. Williamson, K. Iczkowski and I. Members, "The 2019 International Society of Urological Pathology (ISUP) Consensus Conference on Grading of Prostatic Carcinoma.", American Journal of Surgical Pathology, 2020;44(8):e87-e99. Abstract/PDF DOI PMID
  14. K. Murphy, H. Smits, A. Knoops, M. Korst, T. Samson, E. Scholten, S. Schalekamp, C. Schaefer-Prokop, R. Philipsen, A. Meijers, J. Melendez, B. van Ginneken and M. Rutten, "COVID-19 on the Chest Radiograph: A Multi-Reader Evaluation of an AI System", Radiology, 2020:201874. Abstract/PDF DOI PMID Cited by ~12
  15. M. Prokop, W. van Everdingen, T. van Rees Vellinga, J. van Quarles Ufford, L. Stoger, L. Beenen, B. Geurts, H. Gietema, J. Krdzalic, C. Schaefer-Prokop, B. van Ginneken, M. Brink and the COVID-19 Standardized Reporting Working Group of the Dutch Radiological Society, "CO-RADS - A categorical CT assessment scheme for patients with suspected COVID-19: definition and evaluation", Radiology, 2020:201473. Abstract/PDF DOI PMID Cited by ~47
  16. S. Habib, S. Rafiq, S. Zaidi, R. Ferrand, J. Creswell, B. Van Ginneken, W. Jamal, K. Azeemi, S. Khowaja and A. Khan, "Evaluation of computer aided detection of tuberculosis on chest radiography among people with diabetes in Karachi Pakistan", Nature Scientific Reports, 2020;10(1):6276. Abstract DOI PMID
  17. K. Murphy, S. Habib, S. Zaidi, S. Khowaja, A. Khan, J. Melendez, E. Scholten, F. Amad, S. Schalekamp, M. Verhagen, R. Philipsen, A. Meijers and B. van Ginneken, "Computer aided detection of tuberculosis on chest radiographs: An evaluation of the CAD4TB v6 system", Nature Scientific Reports, 2020;10:5492. Abstract/PDF DOI PMID Cited by ~8
  18. B. Liefers, J. Colijn, C. González-Gonzalo, T. Verzijden, J. Wang, N. Joachim, P. Mitchell, C. Hoyng, B. van Ginneken, C. Klaver and C. Sánchez, "A deep learning model for segmentation of geographic atrophy to study its long-term natural history", Ophthalmology, 2020. Abstract/PDF DOI PMID Cited by ~2
  19. M. Balkenhol, W. Vreuls, C. Wauters, S. Mol, J. van der Laak and P. Bult, "Histological subtypes in triple negative breast cancer are associated with specific information on survival", Annals of Diagnostic Pathology, 2020;46:151490. Abstract/PDF DOI PMID
  20. I. Olaciregui-Ruiz, I. Torres-Xirau, J. Teuwen, U. van der Heide and A. Mans, "A Deep Learning-based correction to EPID dosimetry for attenuation and scatter in the Unity MR-Linac system", Physica Medica, 2020;71:124-131. Abstract/PDF DOI PMID
  21. H. Kauczor, A. Baird, T. Blum, L. Bonomo, C. Bostantzoglou, O. Burghuber, B. Čepicka, A. Comanescu, S. Courad, A. Devaraj, V. Jespersen, S. Morozov, I. Agmon, N. Peled, P. Powell, H. Prosch, S. Ravara, J. Rawlinson, M. Revel, M. Silca, A. Snoeckx, B. van Ginneken, J. van Meerbeeck, C. Vardavas, O. von Stackelberg, M. Gaga, O. behalf of the of (ESR) and T. (ERS), "ESR/ERS statement paper on lung cancer screening", European Radiology, 2020. Abstract/PDF DOI PMID
  22. H. Kauczor, A. Baird, T. Blum, L. Bonomo, C. Bostantzoglou, O. Burghuber, B. Čepicka, A. Comanescu, S. Couraud, A. Devaraj, V. Jespersen, S. Morozov, I. Nardi Agmon, N. Peled, P. Powell, H. Prosch, S. Ravara, J. Rawlinson, M. Revel, M. Silva, A. Snoeckx, B. van Ginneken, J. van Meerbeeck, C. Vardavas, O. von Stackelberg, M. Gaga, E. of (ESR) and T. (ERS), "ESR/ERS statement paper on lung cancer screening", European Respiratory Journal, 2020;55(2):1900506. Abstract/PDF DOI PMID Cited by ~5
  23. M. Sieren, F. Brenne, A. Hering, H. Kienapfel, N. Gebauer, T. Oechtering, A. Fürschke, F. Wegner, E. Stahlberg, S. Heldmann, J. Barkhausen and A. Frydrychowicz, "Rapid study assessment in follow-up whole-body computed tomography in patients with multiple myeloma using a dedicated bone subtraction software", European Radiology, 2020. Abstract/PDF DOI PMID
  24. S. van Velzen, N. Lessmann, B. Velthuis, I. Bank, D. van den Bongard, T. Leiner, P. de Jong, W. Veldhuis, A. Correa, J. Terry, J. Carr, M. Viergever, H. Verkooijen and I. Išgum, "Deep learning for automatic calcium scoring in CT: Validation using multiple cardiac CT and chest CT protocols", Radiology, 2020;295(1):66-79. Abstract/PDF DOI PMID Cited by ~10
  25. H. de Koning, C. van der Aalst, P. de Jong, E. Scholten, K. Nackaerts, M. Heuvelmans, J. Lammers, C. Weenink, U. Yousaf-Khan, N. Horeweg, S. van 't Westeinde, M. Prokop, W. Mali, F. Mohamed Hoesein, P. van Ooijen, J. Aerts, M. den Bakker, E. Thunnissen, J. Verschakelen, R. Vliegenthart, J. Walter, K. Ten Haaf, H. Groen and M. Oudkerk, "Reduced Lung-Cancer Mortality with Volume CT Screening in a Randomized Trial", New England Journal of Medicine, 2020;382(6):503-513. Abstract/PDF DOI PMID Cited by ~105
  26. T. Boers, Y. Hu, E. Gibson, D. Barratt, E. Bonmati, J. Krdzalic, F. van der Heijden, J. Hermans and H. Huisman, "Interactive 3D U-net for the Segmentation of the Pancreas in Computed Tomography Scans", Physics in Medicine and Biology, 2020;65(6):065002. Abstract/PDF DOI PMID
  27. N. Mahomed, B. van Ginneken, R. Philipsen, J. Melendez, D. Moore, H. Moodley, T. Sewchuran, D. Mathew and S. Madhi, "Computer-aided diagnosis for World Health Organization-defined chest radiograph primary-endpoint pneumonia in children", Pediatric Radiology, 2020;50(4):482-491. Abstract/PDF DOI PMID Cited by ~3
  28. W. Bulten, H. Pinckaers, H. van Boven, R. Vink, T. de Bel, B. van Ginneken, J. van der Laak, C. de Hulsbergen-van Kaa and G. Litjens, "Automated deep-learning system for Gleason grading of prostate cancer using biopsies: a diagnostic study", Lancet Oncology, 2020;21(2):233-241. Abstract/PDF DOI PMID Cited by ~29
  29. F. Ayatollahi, S. Shokouhi and J. Teuwen, "Differentiating Benign and Malignant Mass and non-Mass Lesions in Breast DCE-MRI using Normalized Frequency-based Features", International Journal of Computer Assisted Radiology and Surgery, 2020;15(2):297-307. Abstract/PDF DOI PMID
  30. C. González-Gonzalo, V. Sánchez-Gutiérrez, P. Hernández-Martínez, I. Contreras, Y. Lechanteur, A. Domanian, B. van Ginneken and C. Sánchez, "Evaluation of a deep learning system for the joint automated detection of diabetic retinopathy and age-related macular degeneration", Acta Ophthalmologica, 2020;98(4):368-377. Abstract/PDF DOI PMID Cited by ~9
  31. S. van de Leemput, M. Prokop, B. van Ginneken and R. Manniesing, "Stacked Bidirectional Convolutional LSTMs for Deriving 3D Non-contrast CT from Spatiotemporal 4D CT", IEEE Transactions on Medical Imaging, 2020;39(4):985-996. Abstract/PDF DOI PMID Cited by ~4
  32. J. van Zelst, T. Tan, R. Mann and N. Karssemeijer, "Validation of radiologists' findings by computer-aided detection (CAD) software in breast cancer detection with automated 3D breast ultrasound: a concept study in implementation of artificial intelligence software", Acta Radiologica, 2020;61(3):312-320. Abstract/PDF DOI PMID
  33. A. Schreuder and C. Schaefer-Prokop, "Perifissural nodules: ready for application into lung cancer CT screening?", Annals of Translational Medicine, 2020. Abstract/PDF DOI
  34. A. Schreuder, E. Scholten, B. van Ginneken and C. Jacobs, "Artificial intelligence for detection and characterization of pulmonary nodules in lung cancer CT screening: ready for practice?", Translational Lung Cancer Research, 2020. Abstract/PDF DOI
  35. 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", Medical Image Analysis, 2020. Abstract/PDF DOI Cited by ~5
  36. M. Meijs, F. Meijer, M. Prokop, B. van Ginneken and R. Manniesing, "Image-level detection of arterial occlusions in 4D-CTA of acute stroke patients using deep learning", Medical Image Analysis, 2020. Abstract/PDF DOI
  37. S. Kazeminia, C. Baur, A. Kuijper, B. van Ginneken, N. Navab, S. Albarqouni and A. Mukhopadhyay, "GANs for Medical Image Analysis", Artificial Intelligence in Medicine, 2020. Abstract arXiv Cited by ~55
  38. M. Amgad, A. Stovgaard, E. Balslev, J. Thagaard, W. Chen, S. Dudgeon, A. Sharma, J. Kerner, C. Denkert, Y. Yuan, K. AbdulJabbar, S. Wienert, P. Savas, L. Voorwerk, A. Beck, A. Madabhushi, J. Hartman, M. Sebastian, H. Horlings, J. Hudeček, F. Ciompi, D. Moore, R. Singh, E. Roblin, M. Balancin, M. Mathieu, J. Lennerz, P. Kirtani, I. Chen, J. Braybrooke, G. Pruneri, S. Demaria, S. Adams, S. Schnitt, S. Lakhani, F. Rojo, L. Comerma, S. Badve, M. Khojasteh, W. Symmans, C. Sotiriou, P. Gonzalez-Ericsson, K. Pogue-Geile, R. Kim, D. Rimm, G. Viale, S. Hewitt, J. Bartlett, F. Penault-Llorca, S. Goel, H. Lien, S. Loibl, Z. Kos, S. Loi, M. Hanna, S. Michiels, M. Kok, T. Nielsen, A. Lazar, Z. Bago-Horvath, L. Kooreman, J. van der Laak, J. Saltz, B. Gallas, U. Kurkure, M. Barnes, R. Salgado and L. Cooper, "Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group", npj Breast Cancer, 2020;6(1). Abstract/PDF DOI Cited by ~2
  39. Z. Kos, A. Roblin, R. Kim, S. Michiels, B. Gallas, W. Chen, K. van de Vijver, S. Goel, S. Adams, S. Demaria, G. Viale, T. Nielsen, S. Badve, W. Symmans, C. Sotiriou, D. Rimm, S. Hewitt, C. Denkert, S. Loibl, S. Luen, J. Bartlett, P. Savas, G. Pruneri, D. Dillon, M. Cheang, A. Tutt, J. Hall, M. Kok, H. Horlings, A. Madabhushi, J. van der Laak, F. Ciompi, A. Laenkholm, E. Bellolio, T. Gruosso, S. Fox, J. Araya, G. Floris, J. Hudeček, L. Voorwerk, A. Beck, J. Kerner, D. Larsimont, S. Declercq, G. den Eynden, L. Pusztai, A. Ehinger, W. Yang, K. AbdulJabbar, Y. Yuan, R. Singh, C. Hiley, M. al Bakir, A. Lazar, S. Naber, S. Wienert, M. Castillo, G. Curigliano, M. Dieci, F. André, C. Swanton, J. Reis-Filho, J. Sparano, E. Balslev, I. Chen, E. Stovgaard, K. Pogue-Geile, K. Blenman, F. Penault-Llorca, S. Schnitt, S. Lakhani, A. Vincent-Salomon, F. Rojo, J. Braybrooke, M. Hanna, M. Soler-Monsó, D. Bethmann, C. Castaneda, K. Willard-Gallo, A. Sharma, H. Lien, S. Fineberg, J. Thagaard, L. Comerma, P. Gonzalez-Ericsson, E. Brogi, S. Loi, J. Saltz, F. Klaushen, L. Cooper, M. Amgad, D. Moore and R. Salgado, "Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer", npj Breast Cancer, 2020;6(1). Abstract/PDF DOI Cited by ~1
  40. A. Schreuder, C. Jacobs, E. Scholten, B. van Ginneken, C. Schaefer-Prokop and M. Prokop, "Typical CT Features of Intrapulmonary Lymph Nodes: A Review", Radiology: Cardiothoracic Imaging, 2020;2(4):e190159. Abstract/PDF DOI
  41. Z. Swiderska-Chadaj, K. Hebeda, M. van den Brand and G. Litjens, "Artificial intelligence to detect MYC translocation in slides of diffuse large B-cell lymphoma", Virchows Archiv, 2020. Abstract/PDF DOI
  42. G. Humpire Mamani, J. Bukala, E. Scholten, M. Prokop, B. van Ginneken and C. Jacobs, "Fully Automatic Volume Measurement of the Spleen at CT Using Deep Learning", Radiology: Artificial Intelligence, 2020;2(4):e190102. Abstract/PDF DOI Cited by ~1 Algorithm
  43. J. Goudsmit and J. Teuwen, "Tussen data en theorie", Tijdschrift voor Toezicht, 2020;11(1):48-53. Abstract/PDF DOI
  44. E. Sogancioglu, K. Murphy, E. Calli, E. Scholten, S. Schalekamp and B. Van Ginneken, "Cardiomegaly Detection on Chest Radiographs: Segmentation Versus Classification", IEEE Access, 2020;8:94631-94642. Abstract/PDF DOI


  1. N. Lessmann and B. van Ginneken, "Random smooth gray value transformations for cross modality learning with gray value invariant networks", arXiv:2003.06158, 2020. Abstract/PDF arXiv
  2. A. Sekuboyina, A. Bayat, M. Husseini, M. Loffler, M. Rempfler, J. Kukacka, G. Tetteh, A. Valentinitsch, C. Payer, D. Stern, M. Urschler, M. Chen, D. Cheng, N. Lessmann, Y. Hu, T. Wang, D. Yang, D. Xu, F. Ambellan, T. Amiranashvili, M. Ehlke, H. Lamecker, S. Lehnert, M. Lirio, N. de Olaguer, H. Ramm, M. Sahu, A. Tack, S. Zachow, T. Jiang, X. Ma, C. Angerman, X. Wang, Q. Wei, K. Brown, M. Wolf, A. Kirszenberg, E. Puybareauq, B. Menze and J. Kirschke, "VerSe: A Vertebrae Labelling and Segmentation Benchmark", arXiv:2001.09193, 2020. Abstract arXiv Cited by ~2
  3. C. de Vente, L. Boulogne, K. Venkadesh, C. Sital, N. Lessmann, C. Jacobs, C. Sánchez and B. van Ginneken, "Improving Automated COVID-19 Grading with Convolutional Neural Networks in Computed Tomography Scans: An Ablation Study", arXiv:2009.09725, 2020. Abstract/PDF arXiv
  4. A. Meyer, G. Chlebus, M. Rak, D. Schindele, M. Schostak, B. van Ginneken, A. Schenk, H. Meine, H. Hahn, A. Schreiber and C. Hansen, "Anisotropic 3D Multi-Stream CNN for Accurate Prostate Segmentation from Multi-Planar MRI", arXiv:2009.11120, 2020. Abstract/PDF arXiv
  5. S. Wetstein, C. González-Gonzalo, G. Bortsova, B. Liefers, F. Dubost, I. Katramados, L. Hogeweg, B. van Ginneken, J. Pluim, M. de Bruijne, C. Sánchez and M. Veta, "Adversarial Attack Vulnerability of Medical Image Analysis Systems: Unexplored Factors", arXiv:2006.06356, 2020. Abstract/PDF arXiv
  6. S. Zhou, H. Greenspan, C. Davatzikos, J. Duncan, B. van Ginneken, A. Madabhushi, J. Prince, D. Rueckert and R. Summers, "A review of deep learning in medical imaging: Image traits, technology trends, case studies with progress highlights, and future promises", arXiv:2008.09104, 2020. Abstract/PDF arXiv

Papers in conference proceedings

  1. K. Michielsen, N. Moriakov, J. Teuwen and I. Sechopoulos, "Deep Learning-based Initialization of Iterative Reconstruction for Breast Tomosynthesis", 6th International Conference on Image Formation in X-Ray Computed Tomography, 2020. Abstract
  2. J. Linmans, J. van der Laak and G. Litjens, "Efficient Out-of-Distribution Detection in Digital Pathology Using Multi-Head Convolutional Neural Networks", Medical Imaging with Deep Learning, 2020:465-478. Abstract/PDF Url
  3. C. Mercan, G. Reijnen-Mooij, D. Martin, J. Lotz, N. Weiss, M. van Gerven and F. Ciompi, "Virtual staining for mitosis detection in Breast Histopathology", IEEE International Symposium on Biomedical Imaging, 2020. Abstract/PDF DOI
  4. A. Hering and S. Heldmann, "mlVIRNET: Improved Deep Learning Registration Using a Coarse to Fine Approach to Capture all Levels of Motion", Bildverarbeitung für die Medizin, 2020:175. Abstract/PDF DOI
  5. Z. Swiderska-Chadaj, K. Hebeda, M. van den Brand and G. Litjens, "Predicting MYC translocation in HE specimens of diffuse large B-cell lymphoma through deep learning", Medical Imaging, 2020;11320:1132010. Abstract/PDF DOI
  6. D. Tellez, D. Hoppener, C. Verhoef, D. Grunhagen, P. Nierop, M. Drozdzal, J. van der Laak and F. Ciompi, "Extending Unsupervised Neural Image Compression With Supervised Multitask Learning", Medical Imaging with Deep Learning, 2020. Abstract/PDF
  7. N. Moriakov, J. Adler and J. Teuwen, "Kernel of CycleGAN as a principal homogeneous space", International Conference on Learning Representations, 2020. Abstract/PDF Url
  8. Z. Swiderska-Chadaj, K. Nurzynska, G. Bartlomiej, K. Grunberg, L. van der Woude, M. Looijen-Salamon, A. Walts, T. Markiewicz, F. Ciompi and A. Gertych, "A deep learning approach to assess the predominant tumor growth pattern in whole-slide images of lung adenocarcinoma", Medical Imaging, 2020;11320:113200D. Abstract/PDF DOI
  9. L. van Eekelen, H. Pinckaers, K. Hebeda and G. Litjens, "Multi-class semantic cell segmentation and classification of aplasia in bone marrow histology images", Medical Imaging, 2020;11320:113200B. Abstract/PDF DOI
  10. H. Altun, G. Chlebus, C. Jacobs, H. Meine, B. van Ginneken and H. Hahn, "Feasibility of End-To-End Trainable Two-Stage U-Net for Detection of Axillary Lymph Nodes in Contrast-Enhanced CT Based Scans on Sparse Annotations", Medical Imaging, 2020:113141C. Abstract/PDF DOI


  1. 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", ISMRM Benelux, 2020. Abstract
  2. J. Bokhorst, F. Ciompi, I. Zlobec, A. Lugli, M. Vieth, R. Kirsch, J. van der Laak and I. Nagtegaal, "Computer-assisted hot-spot selection for tumor budding assessment in colorectal cancer", European Congress of Pathology, 2020. Abstract
  3. C. Mercan, M. Balkenhol, J. Laak and F. Ciompi, "Grading nuclear pleomorphism in breast cancer using deep learning", European Congress of Pathology, 2020. Abstract
  4. C. González-Gonzalo, S. Wetstein, G. Bortsova, B. Liefers, B. van Ginneken and C. Sánchez, "Are adversarial attacks an actual threat for deep learning systems in real-world eye disease screening settings?", European Society of Retina Specialists, 2020. Abstract Url
  5. T. Riepe, M. Hosseinzadeh, P. Brand and H. Huisman, "Anisotropic Deep Learning Multi-planar Automatic Prostate Segmentation", Annual Meeting of the International Society for Magnetic Resonance in Medicine, 2020. Abstract/PDF
  6. B. Liefers, P. Taylor, C. González-Gonzalo, A. Tufail and C. Sánchez, "Achieving expert level performance in quantifying 13 distinctive features of neovascular age-related macular degeneration on optical coherence tomography", European Society of Retina Specialists, 2020. Abstract Url
  7. A. Ardu, B. Liefers, C. de Vente, C. González-Gonzalo, C. Klaver and C. Sánchez, "Artificial Intelligence for the Classification and Quantification of Reticular Pseudodrusen in Multimodal Retinal Images", European Society of Retina Specialists, 2020. Abstract Url
  8. C. de Vente, M. van Grinsven, S. De Zanet, A. Mosinska, R. Sznitman, C. Klaver and C. Sánchez, "Estimating Uncertainty of Deep Neural Networks for Age-related Macular Degeneration Grading using Optical Coherence Tomography", Association for Research in Vision and Ophthalmology, 2020. Abstract
  9. J. Bokhorst, I. Nagtegaal, I. Zlobec, A. Lugli, M. Vieth, R. Kirsch, J. van der Laak and F. Ciompi, "Deep learning based tumor bud detection in pan-cytokeratin stained colorectal cancer whole-slide images", European Congress of Pathology, 2020. Abstract

PhD theses

  1. M. Balkenhol, "Tissue-based biomarker assessment for predicting prognosis of triple negative breast cancer: the additional value of artificial intelligence", 2020. Abstract/PDF Url
  2. M. Meijs, "Automated Image Analysis and Machine Learning to Detect Cerebral Vascular Pathology in 4D-CTA", 2020. Abstract/PDF

Master theses

  1. L. van Eekelen, "Deep learning-based analysis of bone marrow histopathology images", 2020. Abstract/PDF
  2. R. Kluge, "Pneumothorax Detection On Chest Radiographs: A Comparative Analysis Of Public Datasets, Deep Learning Architectures, And Domain Adaptation Via Iterative Self-Training", 2020. Abstract/PDF
  3. T. de Boer, "A feasibility study for Deep Learning Image Guided Guidewire Tracking for Image-guided Interventions", 2020. Abstract/PDF