Publications

2022

Papers in international journals

  1. 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
  2. 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
  3. 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
  4. 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
  5. W. Bulten, K. Kartasalo, P. Chen, P. Ström, 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. Grönberg, H. Samaratunga, B. Delahunt, T. Tsuzuki, T. Häkkinen, 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. Çakır, X. Farré, K. Geronatsiou, V. Molinié, 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
  6. A. Schreuder, C. Jacobs, N. Lessmann, M. Broeders, M. Silva, I. Išgum, 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
  7. R. Vliegenthart, A. Fouras, C. Jacobs and N. Papanikolaou, "Innovations in thoracic imaging: CT, radiomics, AI and x-ray velocimetry", Respirology, 2022.
    Abstract DOI
  8. 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
  9. 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
  10. 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
  11. 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
  12. 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
  13. M. Hermsen, F. Ciompi, A. Adefidipe, A. Denic, A. Dendooven, B. Smith, D. van Midden, J. Bräsen, J. Kers, M. Stegall, P. Bándi, 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.
    Abstract DOI
  14. 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
  15. 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
  16. 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
  17. J. Noothout, N. Lessmann, M. van 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;9(5):052407.
    Abstract DOI

Abstracts

  1. 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
  2. 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
  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. M. Grauw and B. Ginneken, "Semi-supervised 3D universal lesion segmentation in CT thorax-abdomen scans", European Congress of Radiology, 2022.
    Abstract
  5. A. Saha, J. Bosma, J. Twilt, B. van Ginneken, D. Yakar, M. Elschot, J. Veltman, J. Fütterer, 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
  6. 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
  7. C. Roest, T. Kwee, A. Saha, J. Fütterer, D. Yakar and H. Huisman, "AI-Assisted Biparametric MRI Surveillance of Prostate Cancer: Feasibility Study", European Radiology, 2022.
    Abstract DOI
  8. C. Roest, T. Kwee, A. Saha, J. Fütterer, D. Yakar and H. Huisman, "AI-Assisted Biparametric MRI Surveillance of Prostate Cancer: Feasibility Study", European Congress of Radiology, 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. 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

PhD theses

  1. W. Bulten, "Artificial intelligence as a digital fellow in pathology: Human-machine synergy for improved prostate cancer diagnosis", 2022.
    Abstract Url