Publications

2020

Papers in international journals

  1. A. Rossi, M. Hosseinzadeh, M. Bianchini, F. Scarselli and H. Huisman, "Multi-modal siamese network for diagnostically similar lesion retrieval in prostate MRI", IEEE Transactions on Medical Imaging, 2020. Abstract/PDF DOI PMID
  2. B. van Ginneken, "The Potential of Artificial Intelligence to Analyze Chest Radiographs for Signs of COVID-19 Pneumonia", Radiology, 2020:204238. Abstract/PDF DOI PMID
  3. 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", Computer Methods and Programs in Biomedicine, 2020:105821. Abstract/PDF DOI PMID
  4. J. Bartstra, F. Draaisma, S. Zwakenberg, N. Lessmann, J. Wolterink, Y. van der Schouw, P. de Jong and J. Beulens, "Six months vitamin K treatment does not affect systemic arterial calcification or bone mineral density in diabetes mellitus 2", European Journal of Nutrition, 2020. Abstract/PDF DOI PMID
  5. 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
  6. 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
  7. 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 PMID
  8. 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;66:101810. Abstract/PDF DOI PMID
  9. 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;66:101796. Abstract/PDF DOI PMID Cited by ~5
  10. 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
  11. 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 GitHub
  12. 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
  13. 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
  14. 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;39(11):3499-3511. Abstract/PDF DOI PMID
  15. 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
  16. 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
  17. 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
  18. 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 PMID Cited by ~1
  19. 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 PMID Cited by ~2
  20. 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;296:E166–E172. Abstract/PDF DOI PMID Cited by ~12
  21. 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;296:E97–E104. Abstract/PDF DOI PMID Cited by ~47
  22. 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/PDF DOI PMID
  23. 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
  24. C. van 't Klooster, H. Nathoe, J. Hjortnaes, M. Bots, I. Isgum, N. Lessmann, Y. van der Graaf, T. Leiner and F. Visseren, "Multifocal cardiovascular calcification in patients with established cardiovascular disease; prevalence, risk factors, and relation with recurrent cardiovascular disease", International Journal of Cardiology: Heart and Vasculature, 2020;27:100499. Abstract/PDF DOI PMID
  25. 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;127(8):1086-1096. Abstract/PDF DOI PMID Cited by ~2
  26. 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
  27. 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;30:3277-3294. Abstract/PDF DOI PMID
  28. 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
  29. 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;30:3198-3209. Abstract/PDF DOI PMID
  30. 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
  31. 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
  32. 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
  33. 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
  34. 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 Algorithm
  35. 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
  36. 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
  37. M. Dekker, F. Waissi, I. Bank, N. Lessmann, I. Išgum, B. Velthuis, A. Scholtens, G. Leenders, G. Pasterkamp, D. de Kleijn, L. Timmers and A. Mosterd, "Automated calcium scores collected during myocardial perfusion imaging improve identification of obstructive coronary artery disease", International Journal of Cardiology: Heart and Vasculature, 2020;26:100434. Abstract/PDF DOI PMID
  38. C. Celeng, R. Takx, N. Lessmann, P. Maurovich-Horvat, T. Leiner, I. Išgum and P. de Jong, "The association between marital status, coronary computed tomography imaging biomarkers, and mortality in a lung cancer screening population", Journal of Thoracic Imaging, 2020;35:204-209. Abstract/PDF DOI PMID
  39. 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
  40. 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
  41. 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;109:101938. Abstract/PDF DOI Cited by ~55
  42. 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
  43. A. Schreuder and C. Schaefer-Prokop, "Perifissural nodules: ready for application into lung cancer CT screening?", Annals of Translational Medicine, 2020. Abstract/PDF DOI
  44. 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
  45. M. Meijs, S. Pegge, M. Vos, A. Patel, S. van de Leemput, K. Koschmieder, M. Prokop, F. Meijer and R. Manniesing, "Cerebral Artery and Vein Segmentation in Fourdimensional CT Angiography Using Convolutional Neural Networks", Radiology: Artificial Intelligence, 2020;2(4):e190178. Abstract/PDF DOI
  46. 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
  47. 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

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. 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
  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. 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. 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
  6. 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
  7. A. Hering, S. Häger, J. Moltz, N. Lessmann, S. Heldmann and B. van Ginneken, "Constraining Volume Change in Learned Image Registration for Lung CTs", arXiv:2011.14372, 2020. Abstract arXiv

Papers in conference proceedings

  1. N. Moriakov, J. Adler and J. Teuwen, "Kernel of CycleGAN as a principal homogeneous space", International Conference on Learning Representations, 2020. Abstract/PDF Url
  2. 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
  3. A. Saha, P. Prasad and A. Thabit, "Leveraging Adaptive Color Augmentation in Convolutional Neural Networks for Deep Skin Lesion Segmentation", IEEE International Symposium on Biomedical Imaging, 2020:2014-2017. Abstract DOI
  4. 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
  5. 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
  6. A. Saha, F. Tushar, K. Faryna, V. D'Anniballe, R. Hou, M. Mazurowski, G. Rubin and J. Lo, "Weakly Supervised 3D Classification of Chest CT using Aggregated Multi-Resolution Deep Segmentation Features", Medical Imaging, 2020;11314:39 - 44. Abstract DOI
  7. 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, 2020:1770-1774. Abstract/PDF DOI
  8. A. Saha, M. Hosseinzadeh and H. Huisman, "Encoding Clinical Priori in 3D Convolutional Neural Networks for Prostate Cancer Detection in bpMRI", Medical Imaging Meets NeurIPS Workshop - 34th Conference on Neural Information Processing Systems (NeurIPS), 2020. Abstract arXiv
  9. 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
  10. 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
  11. Z. Swiderska-Chadaj, E. Stoelinga, A. Gertych and F. Ciompi, "Multi-Patch Blending improves lung cancer growth pattern segmentation in whole-slide images", IEEE International Conference on Computational Problems of Electrical Engineering, 2020. Abstract/PDF DOI
  12. 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
  13. 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
  14. 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. C. Mercan, M. Balkenhol, J. Laak and F. Ciompi, "Grading nuclear pleomorphism in breast cancer using deep learning", European Congress of Pathology, 2020. Abstract
  2. 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
  3. 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
  4. C. Jacobs, "The role of artificial intelligence in lung cancer screening", European Respiratory Society International Congress, 2020. Abstract
  5. 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
  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. 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
  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. 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
  10. K. Venkadesh, A. Setio, Z. Saghir, B. van Ginneken and C. Jacobs, "Deep Learning for Lung Nodule Malignancy Prediction: Comparison With Clinicians and the Brock Model on an Independent Dataset From a Large Lung Screening Trial", Annual Meeting of the Radiological Society of North America, 2020. Abstract
  11. C. Jacobs, "The role of artificial intelligence in lung cancer screening", Annual Meeting of the Radiological Society of North America, 2020. Abstract
  12. 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

PhD theses

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

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. Payer, "AI-assisted PD-L1 scoring in non-small-cell lung cancer", 2020. Abstract/PDF
  3. L. van Eekelen, "Deep learning-based analysis of bone marrow histopathology images", 2020. Abstract/PDF
  4. A. Saha, "Computer-Aided Detection of Clinically Significant Prostate Cancer in mpMRI", 2020. Abstract
  5. T. de Boer, "A feasibility study for Deep Learning Image Guided Guidewire Tracking for Image-guided Interventions", 2020. Abstract/PDF

Other publications

  1. J. Petersen, R. Estépar, A. Schmidt-Richberg, S. Gerard, B. Lassen-Schmidt, C. Jacobs, R. Beichel and K. Mori, "Thoracic Image Analysis", 2020;12502. Abstract/PDF DOI