Publications

2020

Papers in international journals

  1. 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;20:1. Abstract/PDF DOI PMID
  2. 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
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. 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
  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 arXiv Cited by ~5
  10. 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
  11. A. Schreuder and C. Schaefer-Prokop, "Perifissural nodules: ready for application into lung cancer CT screening?", Annals of Translational Medicine, 2020. Abstract/PDF DOI
  12. 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;98:368-377. Abstract/PDF DOI PMID Cited by ~9
  13. 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 t. of the 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
  14. 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. Abstract/PDF DOI Cited by ~2
  15. 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. Abstract/PDF DOI Cited by ~1
  16. 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
  17. 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
  18. 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
  19. 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 arXiv Cited by ~29
  20. 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:e190102. Abstract/PDF DOI Cited by ~1
  21. N. Lessmann, C. Sanchez, 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
  22. 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
  23. 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
  24. 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
  25. 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 arXiv Cited by ~5
  26. 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
  27. 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
  28. 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 arXiv Cited by ~2
  29. 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
  30. 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
  31. 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
  32. 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;295:66-79. Abstract/PDF DOI PMID Cited by ~10
  33. 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 arXiv Cited by ~8
  34. 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
  35. J. Goudsmit and J. Teuwen, "Tussen data en theorie", Tijdschrift voor Toezicht, 2020;11:48-53. Abstract/PDF DOI
  36. 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;65:065002. Abstract/PDF DOI PMID
  37. 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
  38. 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
  39. 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:e190159. Abstract/PDF DOI
  40. 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

Preprints

  1. 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
  2. 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
  3. 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
  4. 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

Papers in conference proceedings

  1. Z. Swiderska-Chadaj, K. Nurzynska, G. Bartlomiej, K. Grünberg, 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
  2. 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
  3. N. Moriakov, J. Adler and J. Teuwen, "Kernel of CycleGAN as a principal homogeneous space", International Conference on Learning Representations, 2020. Abstract/PDF
  4. 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
  5. 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
  6. 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
  7. 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

Abstracts

  1. 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
  2. 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
  3. 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
  4. 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
  5. C. Mercan, M. Balkenhol, J. Laak and F. Ciompi, "Grading nuclear pleomorphism in breast cancer using deep learning", European Congress of Pathology, 2020. Abstract

PhD theses

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

Master theses

  1. 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
  2. T. de Boer, "A feasibility study for Deep Learning Image Guided Guidewire Tracking for Image-guided Interventions", 2020. Abstract/PDF