Publications

2022

Papers in international journals

  1. M. Aubreville, N. Stathonikos, C. Bertram, R. Klopfleisch, N. Ter Hoeve, F. Ciompi, F. Wilm, C. Marzahl, T. Donovan, A. Maier, J. Breen, N. Ravikumar, Y. Chung, J. Park, R. Nateghi, F. Pourakpour, R. Fick, S. Ben Hadj, M. Jahanifar, A. Shephard, J. Dexl, T. Wittenberg, S. Kondo, M. Lafarge, V. Koelzer, J. Liang, Y. Wang, X. Long, J. Liu, S. Razavi, A. Khademi, S. Yang, X. Wang, R. Erber, A. Klang, K. Lipnik, P. Bolfa, M. Dark, G. Wasinger, M. Veta and K. Breininger, "Mitosis domain generalization in histopathology images - The MIDOG challenge.", Medical Image Analysis, 2022;84:102699.
    Abstract DOI PMID
  2. E. Calli, B. Van Ginneken, E. Sogancioglu and K. Murphy, "FRODO: An in-depth analysis of a system to reject outlier samples from a trained neural network.", IEEE transactions on medical imaging, 2022;PP.
    Abstract DOI PMID
  3. C. Mercan, M. Balkenhol, R. Salgado, M. Sherman, P. Vielh, W. Vreuls, A. Polónia, H. Horlings, W. Weichert, J. Carter, P. Bult, M. Christgen, C. Denkert, K. van de Vijver, J. Bokhorst, J. van der Laak and F. Ciompi, "Deep learning for fully-automated nuclear pleomorphism scoring in breast cancer.", NPJ breast cancer, 2022;8(1):120.
    Abstract DOI PMID
  4. S. Marchesin, F. Giachelle, N. Marini, M. Atzori, S. Boytcheva, G. Buttafuoco, F. Ciompi, G. Di Nunzio, F. Fraggetta, O. Irrera, H. Müller, T. Primov, S. Vatrano and G. Silvello, "Empowering digital pathology applications through explainable knowledge extraction tools.", Journal of pathology informatics, 2022;13:100139.
    Abstract DOI PMID
  5. N. Harlianto, J. Westerink, M. Hol, R. Wittenberg, W. Foppen, P. van der Veen, B. van Ginneken, J. Verlaan, P. de Jong, F. Mohamed Hoesein and UCC-SMART Study Group , "Patients with diffuse idiopathic skeletal hyperostosis have an increased burden of thoracic aortic calcifications", Rheumatology Advances in Practice, 2022;6(2):rkac060.
    Abstract DOI PMID
  6. E. Munari, G. Querzoli, M. Brunelli, M. Marconi, M. Sommaggio, M. Cocchi, G. Martignoni, G. Netto, A. Caliò, L. Quatrini, F. Mariotti, C. Luchini, I. Girolami, A. Eccher, D. Segala, F. Ciompi, G. Zamboni, L. Moretta and G. Bogina, "Comparison of three validated PD-L1 immunohistochemical assays in urothelial carcinoma of the bladder: interchangeability and issues related to patient selection.", Frontiers in immunology, 2022;13:954910.
    Abstract DOI PMID
  7. E. Calli, K. Murphy, E. Scholten, S. Schalekamp and B. van Ginneken, "Explainable emphysema detection on chest radiographs with deep learning", PLoS One, 2022;17(7):e0267539.
    Abstract DOI PMID
  8. N. Marini, S. Marchesin, S. Otálora, M. Wodzinski, A. Caputo, M. van Rijthoven, W. Aswolinskiy, J. Bokhorst, D. Podareanu, E. Petters, S. Boytcheva, G. Buttafuoco, S. Vatrano, F. Fraggetta, J. van der Laak, M. Agosti, F. Ciompi, G. Silvello, H. Muller and M. Atzori, "Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations.", NPJ digital medicine, 2022;5(1):102.
    Abstract DOI PMID
  9. M. Hermsen, F. Ciompi, A. Adefidipe, A. Denic, A. Dendooven, B. Smith, D. van Midden, J. Brasen, J. Kers, M. Stegall, P. Bandi, T. Nguyen, Z. Swiderska-Chadaj, B. Smeets, L. Hilbrands and J. van der Laak, "Convolutional neural networks for the evaluation of chronic and inflammatory lesions in kidney transplant biopsies", American Journal of Pathology, 2022;192(10):1418-1432.
    Abstract DOI PMID
  10. L. Adams, M. Makowski, G. Engel, M. Rattunde, F. Busch, P. Asbach, S. Niehues, S. Vinayahalingam, B. van Ginneken, G. Litjens and K. Bressem, "Prostate158 - An expert-annotated 3T MRI dataset and algorithm for prostate cancer detection", Computers in Biology and Medicine, 2022;148:105817.
    Abstract DOI PMID
  11. M. Antonelli, A. Reinke, S. Bakas, K. Farahani, A. Kopp-Schneider, B. Landman, G. Litjens, B. Menze, O. Ronneberger, R. Summers, B. van Ginneken, M. Bilello, P. Bilic, P. Christ, R. Do, M. Gollub, S. Heckers, H. Huisman, W. Jarnagin, M. McHugo, S. Napel, J. Pernicka, K. Rhode, C. Tobon-Gomez, E. Vorontsov, J. Meakin, S. Ourselin, M. Wiesenfarth, P. Arbelaez, B. Bae, S. Chen, L. Daza, J. Feng, B. He, F. Isensee, Y. Ji, F. Jia, I. Kim, K. Maier-Hein, D. Merhof, A. Pai, B. Park, M. Perslev, R. Rezaiifar, O. Rippel, I. Sarasua, W. Shen, J. Son, C. Wachinger, L. Wang, Y. Wang, Y. Xia, D. Xu, Z. Xu, Y. Zheng, A. Simpson, L. Maier-Hein and M. Cardoso, "The Medical Segmentation Decathlon", Nature Communications, 2022;13(1):4128.
    Abstract DOI PMID
  12. G. Litjens, F. Ciompi and J. van der Laak, "A Decade of GigaScience: The Challenges of Gigapixel Pathology Images.", GigaScience, 2022;11.
    Abstract DOI PMID Download
  13. H. Pinckaers, J. van Ipenburg, J. Melamed, A. De Marzo, E. Platz, B. van Ginneken, J. van der Laak and G. Litjens, "Predicting biochemical recurrence of prostate cancer with artificial intelligence", Communications Medicine, 2022;2:64.
    Abstract DOI PMID
  14. K. Koschmieder, M. Paul, T. van den Heuvel, A. van der Eerden, B. van Ginneken and R. Manniesing, "Automated detection of cerebral microbleeds via segmentation in susceptibility-weighted images of patients with traumatic brain injury", NeuroImage: Clinical, 2022;35:103027.
    Abstract DOI PMID
  15. C. de Vente, L. Boulogne, K. Venkadesh, C. Sital, N. Lessmann, C. Jacobs, C. Sánchez and B. van Ginneken, "Automated COVID-19 Grading with Convolutional Neural Networks in Computed Tomography Scans: A Systematic Comparison", IEEE Transactions on Artificial Intelligence, 2022;3(2):129-138.
    Abstract DOI PMID Download
  16. I. Girolami, L. Pantanowitz, S. Marletta, M. Hermsen, J. van der Laak, E. Munari, L. Furian, F. Vistoli, G. Zaza, M. Cardillo, L. Gesualdo, G. Gambaro and A. Eccher, "Artificial intelligence applications for pre-implantation kidney biopsy pathology practice: a systematic review.", Journal of nephrology, 2022.
    Abstract DOI PMID
  17. E. Sogancioglu, K. Murphy, E. Th Scholten, L. Boulogne, M. Prokop and B. van Ginneken, "Automated estimation of total lung volume using chest radiographs and deep learning", Medical Physics, 2022;49(7):4466-4477.
    Abstract DOI PMID
  18. S. Satturwar, I. Girolami, E. Munari, F. Ciompi, A. Eccher and L. Pantanowitz, "Program death ligand-1 immunocytochemistry in lung cancer cytological samples: A systematic review.", Diagnostic cytopathology, 2022;50(6):313-323.
    Abstract DOI PMID
  19. M. Schilpzand, C. Neff, J. van Dillen, B. van Ginneken, T. Heskes, C. de Korte and T. van den Heuvel, "Automatic Placenta Localization From Ultrasound Imaging in a Resource-Limited Setting Using a Predefined Ultrasound Acquisition Protocol and Deep Learning.", Ultrasound in medicine & biology, 2022;48(4):663-674.
    Abstract DOI PMID
  20. W. Bulten, K. Kartasalo, P. Chen, P. Strom, H. Pinckaers, K. Nagpal, Y. Cai, D. Steiner, H. van Boven, R. Vink, C. de Hulsbergen-van Kaa, J. van der Laak, M. Amin, A. Evans, T. van der Kwast, R. Allan, P. Humphrey, H. Gronberg, H. Samaratunga, B. Delahunt, T. Tsuzuki, T. Hakkinen, L. Egevad, M. Demkin, S. Dane, F. Tan, M. Valkonen, G. Corrado, L. Peng, C. Mermel, P. Ruusuvuori, G. Litjens, M. Eklund, A. Brilhante, A. Cakir, X. Farre, K. Geronatsiou, V. Molinie, G. Pereira, P. Roy, G. Saile, P. Salles, E. Schaafsma, J. Tschui, J. Billoch-Lima, E. Pereira, M. Zhou, S. He, S. Song, Q. Sun, H. Yoshihara, T. Yamaguchi, K. Ono, T. Shen, J. Ji, A. Roussel, K. Zhou, T. Chai, N. Weng, D. Grechka, M. Shugaev, R. Kiminya, V. Kovalev, D. Voynov, V. Malyshev, E. Lapo, M. Campos, N. Ota, S. Yamaoka, Y. Fujimoto, K. Yoshioka, J. Juvonen, M. Tukiainen, A. Karlsson, R. Guo, C. Hsieh, I. Zubarev, H. Bukhar, W. Li, J. Li, W. Speier, C. Arnold, K. Kim, B. Bae, Y. Kim, H. Lee, J. Park and the PANDA challenge consortium, "Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge", Nature Medicine, 2022.
    Abstract DOI PMID
  21. A. Schreuder, C. Jacobs, N. Lessmann, M. Broeders, M. Silva, I. Isgum, P. de Jong, M. van den Heuvel, N. Sverzellati, M. Prokop, U. Pastorino, C. Schaefer-Prokop and B. van Ginneken, "Scan-based competing death risk model for reevaluating lung cancer computed tomography screening eligibility", European Respiratory Journal, 2022;59(5):2101613.
    Abstract DOI PMID Download
  22. M. D'Amato, P. Szostak and B. Torben-Nielsen, "A Comparison Between Single- and Multi-Scale Approaches for Classification of Histopathology Images", Frontiers in Public Health, 2022;10.
    Abstract DOI
  23. N. Alves, M. Schuurmans, G. Litjens, J. Bosma, J. Hermans and H. Huisman, "Fully Automatic Deep Learning Framework for Pancreatic Ductal Adenocarcinoma Detection on Computed Tomography", Cancers, 2022:376.
    Abstract DOI Download
  24. P. Bilic, P. Christ, H. Li, E. Vorontsov, A. Ben-Cohen, G. Kaissis, A. Szeskin, C. Jacobs, G. Mamani, G. Chartrand, F. Lohöfer, J. Holch, W. Sommer, F. Hofmann, A. Hostettler, N. Lev-Cohain, M. Drozdzal, M. Amitai, R. Vivanti, J. Sosna, I. Ezhov, A. Sekuboyina, F. Navarro, F. Kofler, J. Paetzold, S. Shit, X. Hu, J. Lipková, M. Rempfler, M. Piraud, J. Kirschke, B. Wiestler, Z. Zhang, C. Hülsemeyer, M. Beetz, F. Ettlinger, M. Antonelli, W. Bae, M. Bellver, L. Bi, H. Chen, G. Chlebus, E. Dam, Q. Dou, C. Fu, B. Georgescu, X. Giró-i-Nieto, F. Gruen, X. Han, P. Heng, J. Hesser, J. Moltz, C. Igel, F. Isensee, P. Jäger, F. Jia, K. Kaluva, M. Khened, I. Kim, J. Kim, S. Kim, S. Kohl, T. Konopczynski, A. Kori, G. Krishnamurthi, F. Li, H. Li, J. Li, X. Li, J. Lowengrub, J. Ma, K. Maier-Hein, K. Maninis, H. Meine, D. Merhof, A. Pai, M. Perslev, J. Petersen, J. Pont-Tuset, J. Qi, X. Qi, O. Rippel, K. Roth, I. Sarasua, A. Schenk, Z. Shen, J. Torres, C. Wachinger, C. Wang, L. Weninger, J. Wu, D. Xu, X. Yang, S. Yu, Y. Yuan, M. Yue, L. Zhang, J. Cardoso, S. Bakas, R. Braren, V. Heinemann, C. Pal, A. Tang, S. Kadoury, L. Soler, B. van Ginneken, H. Greenspan, L. Joskowicz and B. Menze, "The Liver Tumor Segmentation Benchmark (LiTS)", Medical Image Analysis, 2022:102680.
    Abstract DOI
  25. S. Labus, M. Altmann, H. Huisman, A. Tong, T. Penzkofer, M. Choi, I. Shabunin, D. Winkel, P. Xinga, D. Szolar, S. Shea, R. Grimm, H. von Busch, A. Kamen, T. Herold and C. Baumann, "A concurrent, deep learning-based computer-aided detection system for prostate multiparametric MRI: a performance study involving experienced and less-experienced radiologists", European Radiology, 2022.
    Abstract DOI
  26. B. van Ginneken, "Tuberculosis Detection from Chest Radiographs: Stop Training Radiologists Now", Radiology, 2022;00:1-2.
    Abstract DOI
  27. J. Bleker, T. Kwee, D. Rouw, C. Roest, J. Borstlap, I. de Jong, R. Dierckx, H. Huisman and D. Yakar, "A deep learning masked segmentation alternative to manual segmentation in biparametric MRI prostate cancer radiomics", European Radiology, 2022:1-10.
    Abstract
  28. M. Sunoqrot, A. Saha, M. Hosseinzadeh, M. Elschot and H. Huisman, "Artificial Intelligence for Prostate MRI: Open Datasets, Available Applications, and Grand Challenges", European Radiology Experimental, 2022:35.
    Abstract DOI
  29. J. Noothout, N. Lessmann, M. Eede, L. van Harten, E. Sogancioglu, F. Heslinga, M. Veta, B. van Ginneken and I. Isgum, "Knowledge distillation with ensembles of convolutional neural networks for medical image segmentation", Journal of Medical Imaging, 2022.
    Abstract DOI
  30. R. Vliegenthart, A. Fouras, C. Jacobs and N. Papanikolaou, "Innovations in thoracic imaging: CT, radiomics, AI and x-ray velocimetry", Respirology, 2022.
    Abstract DOI
  31. M. Schuurmans, N. Alves, P. Vendittelli, H. Huisman and J. Hermans, "Setting the Research Agenda for Clinical Artificial Intelligence in Pancreatic Adenocarcinoma Imaging", Cancers, 2022:3498.
    Abstract DOI
  32. C. Roest, T. Kwee, A. Saha, J. Futterer, D. Yakar and H. Huisman, "AI-Assisted Biparametric MRI Surveillance of Prostate Cancer: Feasibility Study", European Radiology, 2022.
    Abstract DOI
  33. M. Huisman and N. Lessmann, "Automatic Brand Identification of Orthopedic Implants from Radiographs: Ready for the Next Step?", Radiology: Artificial Intelligence, 2022;4(2):e220008.
    Abstract DOI
  34. M. Schaap, N. Cardozo, A. Patel, E. de Jong, B. van Ginneken and M. Seyger, "Image-based automated Psoriasis Area Severity Index scoring by Convolutional Neural Networks", Journal of the European Academy of Dermatology and Venereology, 2022;36(1):68-75.
    Abstract DOI Download

Papers in conference proceedings

  1. L. Studer, J. Bokhorst, F. Ciompi, A. Fischer and H. Dawson, "Building-T-cell score is a potential predictor for more aggressive treatment in pT1 colorectal cancers", Proceedings of the ECDP 2022 18th European Congress on Digital Pathology, 2022.
    Abstract
  2. E. Chelebian and F. Ciompi, "Seeded iterative clustering for histology region identification", Learning Meaningful Representations of Life, NeurIPS 2022, 2022.
    Abstract

Abstracts

  1. N. Alves, J. Bosma and H. Huisman, "Towards Safe Clinical Use of Artificial Intelligence for Cancer Detection Through Uncertainty Quantification", Annual Meeting of the Radiological Society of North America, 2022.
    Abstract
  2. T. Perik, J. Hermans and H. Huisman, "AI-assisted analysis of CT perfusion to predict response in patients with pancreatic adenocarcinoma", European Congress of Radiology, 2022.
    Abstract
  3. K. Venkadesh, T. Aleef, A. Schreuder, E. Scholten, B. van Ginneken, M. Prokop and C. Jacobs, "Deep learning for estimating pulmonary nodule malignancy risk using prior CT examinations in lung cancer screening", European Congress of Radiology, 2022.
    Abstract
  4. S. de Jong, N. Alves, M. Schuurmans, J. Hermans and H. Huisman, "Deep Learning for Automatic Contrast Enhancement Phase Detection on Abdominal Computed Tomography", Annual Meeting of the Radiological Society of North America, 2022.
    Abstract
  5. M. Grauw, B. Ginneken, B. Geisler, E. Smit, M. Rooij, S. Schalekamp and M. Prokop, "Deep learning universal lesion segmentation for automated RECIST measurements on CT: comparison to manual assessment by radiologists", European Congress of Radiology, 2022.
    Abstract
  6. E. Aarntzen, E. Genugten, B. Piet, G. Schreibelt, T. Oorschot, G. den Heuvel, F. Ciompi, C. Jacobs, J. Vries and M. den Heuvel, "Imaging tumor-infiltrating CD8 (+) T-cells in non-small cell lung cancer patients upon neo-adjuvant treatment with durvalumab", EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2022.
    Abstract
  7. C. Roest, T. Kwee, A. Saha, J. Futterer, D. Yakar and H. Huisman, "AI-Assisted Biparametric MRI Surveillance of Prostate Cancer: Feasibility Study", European Congress of Radiology, 2022.
    Abstract
  8. L. van Eekelen, E. Munari, I. Girolami, A. Eccher, J. van der Laak, K. Grünberg, M. Looijen-Salamon, S. Vos and F. Ciompi, "Inter-rater agreement of pathologists on determining PD-L1 status in non-small cell lung cancer", European Congress of Pathology, 2022.
    Abstract
  9. M. Grauw and B. Ginneken, "Semi-supervised 3D universal lesion segmentation in CT thorax-abdomen scans", European Congress of Radiology, 2022.
    Abstract
  10. M. Schuurmans, N. Alves, H. Huisman and J. Hermans, "Deep Learning for Detection of Iso-attenuating Pancreatic Adenocarcinoma in Computed Tomography", Annual Meeting of the Radiological Society of North America, 2022.
    Abstract
  11. L. van Eekelen, E. Munari, L. Meesters, G. de Souza, M. Demirel-Andishmand, D. Zegers, M. Looijen-Salamon, S. Vos and F. Ciompi, "Nuclei detection with YOLOv5 in PD-L1 stained non-small cell lung cancer whole slide images", European Congress of Pathology, 2022.
    Abstract
  12. A. Saha, J. Bosma, J. Twilt, B. van Ginneken, D. Yakar, M. Elschot, J. Veltman, J. Futterer, M. de Rooij and H. Huisman, "Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI: The PI-CAI Challenge", Annual Meeting of the Radiological Society of North America, 2022.
    Abstract
  13. J. Spronck, L. Eekelen, L. Tessier, J. Bogaerts, L. van der Woude, M. van den Heuvel, W. Theelen and F. Ciompi, "Deep learning-based quantification of immune infiltrate for predicting response to pembrolizumab from pre-treatment biopsies of metastatic non-small cell lung cancer: A study on the PEMBRO-RT phase II trial", Immuno-Oncology and Technology, 2022.
    Abstract
  14. L. Boulogne and B. van Ginneken, "Automatically Generated CT Severity Scores for COVID-19 Predict Death or Intubation at 1-Month Follow-Up", Annual Meeting of the Radiological Society of North America, 2022.
    Abstract

PhD theses

  1. B. Liefers, "Deep Learning Algorithms for Age-Related Macular Degeneration", PhD thesis, 2022.
    Abstract Url
  2. A. Hering, "Deep-Learning-Based Image Registration and Tumor Follow-Up Analysis", PhD thesis, 2022.
    Abstract Url
  3. W. Bulten, "Artificial intelligence as a digital fellow in pathology: Human-machine synergy for improved prostate cancer diagnosis", PhD thesis, 2022.
    Abstract Url
  4. G. Chlebus, "Deep Learning-Based Segmentation in Multimodal Abdominal Imaging", PhD thesis, 2022.
    Abstract Url

Master theses

  1. S. Vyawahare, "Automated Cephalometric Analysis on Lateral Headplates for Orthodontic Diagnosis", Master thesis, 2022.
    Abstract
  2. S. Adilina, A. Saha and H. Huisman, "Domain Generalization for Prostate Cancer Detection in MRI", Master thesis, 2022.
    Abstract Url
  3. A. Archit and B. van Ginneken, "Automated Abdominal Aortic Aneurysm Detection on CT Scans", Master thesis, 2022.
    Abstract
  4. M. Botros, "Automated Detection and Assessment of Vertebral Fractures in CT Images", Master thesis, 2022.
    Abstract