Publications

2022

Papers in international journals

  1. 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
  2. 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
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. 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
  9. 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
  10. 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
  11. 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
  12. 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
  13. 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
  14. 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
  15. 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
  16. 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
  17. 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
  18. 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
  19. J. Noothout, N. Lessmann, M. Eede, L. van Harten, E. Sogancioglu, F. Heslinga, M. Veta, B. van Ginneken and I. Išgum, "Knowledge distillation with ensembles of convolutional neural networks for medical image segmentation", Journal of Medical Imaging, 2022.
    Abstract DOI
  20. 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
  21. 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
  22. 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
  23. 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
  24. R. Vliegenthart, A. Fouras, C. Jacobs and N. Papanikolaou, "Innovations in thoracic imaging: CT, radiomics, AI and x-ray velocimetry", Respirology, 2022.
    Abstract DOI
  25. 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
  26. B. van Ginneken, "Tuberculosis Detection from Chest Radiographs: Stop Training Radiologists Now", Radiology, 2022;00:1-2.
    Abstract DOI
  27. 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
  28. 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

Abstracts

  1. 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
  2. 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
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. 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
  9. 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
  10. M. Grauw and B. Ginneken, "Semi-supervised 3D universal lesion segmentation in CT thorax-abdomen scans", European Congress of Radiology, 2022.
    Abstract

PhD theses

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

Master theses

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