Publications

2025

Papers in international journals

1. R. Lomans, V. Angerilli, J. Spronck, L. Kodach, I. Gullo, F. Carneiro, R. van der Post and F. Ciompi, "Deep learning for multiclass tumor cell detection in histopathology slides of hereditary diffuse gastric cancer", iScience, 2025;28:113064.
   DOI PMID
2. M. Tran, P. Schmidle, R. Guo, S. Wagner, V. Koch, V. Lupperger, B. Novotny, D. Murphree, H. Hardway, M. D'Amato, J. Lefkes, D. Geijs, A. Feuchtinger, A. Böhner, R. Kaczmarczyk, T. Biedermann, A. Amir, A. Mooyaart, F. Ciompi, G. Litjens, C. Wang, N. Comfere, K. Eyerich, S. Braun, C. Marr and T. Peng, "Generating dermatopathology reports from gigapixel whole slide images with HistoGPT", Nature Communications, 2025;16.
   Abstract DOI PMID
3. D. van Midden, L. Studer, M. Hermsen, E. Steenbergen, J. Kers, N. Kozakowski, Z. Kikic, L. Hilbrands and J. van der Laak, "Deep learning-based histopathologic segmentation of peritubular capillaries in kidney transplant biopsies", Computers in biology and medicine, 2025;193:110395.
   DOI PMID
4. M. Schuurmans, A. Saha, N. Alves, P. Vendittelli, D. Yakar, S. Sabroso-Lasa, N. Xue, N. Malats, H. Huisman, J. Hermans and G. Litjens, "End-to-end prognostication in pancreatic cancer by multimodal deep learning: a retrospective, multicenter study", European Radiology, 2025.
   Abstract DOI PMID
5. J.S. Bosma, K. Dercksen, L. Builtjes, R. André, C. Roest, S. Fransen, C. Noordman, M. Navarro-Padilla, J. Lefkes, N. Alves, M. de Grauw, L. van Eekelen, J. Spronck, M. Schuurmans, B. de Wilde, W. Hendrix, W. Aswolinskiy, A. Saha, J. Twilt, D. Geijs, J. Veltman, D. Yakar, M. de Rooij, F. Ciompi, A. Hering, J. Geerdink, H. Huisman, O. behalf of the consortium, M. de Grauw, L. van Eekelen, B. de Wilde, Q. van Lohuizen, M. Stegeman, K. Rutten, I. Smit, G. Stultiens, C. Overduin, M. Rutten, E. Scholten, R. van der Post, K. Grünberg, S. Vos, E. Taken, I. Nagtegaal, A. Mickan, M. Groeneveld, P. Gerke, J. Meakin, M. Looijen-Salamon, T. de Haas, F. Hoitsma, M. D'Amato and M. de Rooij, "The DRAGON benchmark for clinical NLP", npj Digital Medicine, 2025;8.
   Abstract DOI PMID
6. T. Haddad, J. Bokhorst, L. van den Dobbelsteen, S. Öztürk, E. Baumann, S. van Vliet, K. Verrijp, N. Jamieson, C. Wood, M. Berger, R. Kirsch, M. Aben, N. Rutgers, H. Ueno, F. Ciompi, F. Simmer, J. van der Laak, A. Lugli, I. Zlobec and I. Nagtegaal, "Tumor budding and poorly differentiated clusters as a biological continuum in colorectal cancer invasion and prognosis", Scientific Reports, 2025;15.
   Abstract DOI PMID
7. A. Farris, J. van der Laak and D. van Midden, "Artificial intelligence-enhanced interpretation of kidney transplant biopsy: focus on rejection", Current Opinion in Organ Transplantation, 2025.
   Abstract DOI PMID
8. A. Frei, A. Khan, R. Oberson, S. Reinhard, Y. Banz, F. Meeuwsen, A. Janowczyk, R. Grobholz, H. Dawson, A. Lugli, M. Ilié, J. van der Laak and I. Zlobec, "Computer-aided tumor cell fraction (TCF) estimation by medical students, residents, and pathologists improves inter-observer agreement while highlighting the risk of automation bias", Virchows Archiv, 2025.
   Abstract DOI
9. T. Gootzen, A. Bouwmeester, J. de Hullu, J. Piek, J. van der Laak, M. Simons and M. Steenbeek, "Pathogenesis of peritoneal high-grade serous carcinoma after risk-reducing surgery: a systematic review", The Journal of Pathology: Clinical Research, 2025;11.
   Abstract DOI
10. C. Grisi, K. Kartasalo, M. Eklund, L. Egevad, J. van der Laak and G. Litjens, "Hierarchical Vision Transformers for prostate biopsy grading: Towards bridging the generalization gap", Medical Image Analysis, 2025;105:103663.
    DOI
11. W. Aswolinskiy, R. van der Post, M. Campora, C. Baronchelli, L. Ardighieri, S. Vatrano, J. van der Laak, E. Munari, M. Simons, I. Nagtegaal and F. Ciompi, "Attention-Based Whole-Slide Image Compression Achieves Pathologist-Level Prescreening of Multiorgan Routine Histopathology Biopsies", Modern Pathology, 2025;38(11):100827.
    Abstract DOI
12. G. Koons, "Toward Sex-Specific Biomaterials Innovation: A Perspective", ACS Biomaterials Science & Engineering, 2025;11(9):5131-5144.
    Abstract DOI
13. R. van den Elshout, J. Schoenmakers, A. Veltien, L. Boer, B. Küsters, G. Litjens, F. Meijer, A. van der Kolk, T. Scheenen, M. Wiesmann and D. Henssen, "Post-mortem 11.7 T DTI validation of myeloarchitectural changes in glioblastoma infiltration: Correlation with histology and PLI", Brain Research Bulletin, 2025;230:111526.
    DOI

Preprints

1. S. Sun, L. Tessier, F. Meeuwsen, C. Grisi, D. van Midden, G. Litjens and C. Baumgartner, "Label-free Concept Based Multiple Instance Learning for Gigapixel Histopathology", arXiv:2501.02922, 2025.
   Abstract DOI arXiv
2. S. Sun, D. van Midden, G. Litjens and C. Baumgartner, "Prototype-Based Multiple Instance Learning for Gigapixel Whole Slide Image Classification", arXiv:2503.08384, 2025.
   Abstract DOI arXiv
3. M. van Rijthoven, W. Aswolinskiy, L. Tessier, M. Balkenhol, J. Bogaerts, D. Drubay, L. Blesa, D. Peeters, E. Stovgaard, A. L\aenkholm , H. Haynes, L. Craciun, D. Larsimont, M. Amgad, L. Cooper, C. de Kock, V. Dechering, J. Lotz, N. Weiss, M. van Bockstal, C. Galant, E. Lips, H. Horlings, J. Wesseling, L. Mulder, S. van den Belt, K. Weber, P. Jank, C. Denkert, E. Munari, G. Bogina, C. Russ, A. Lemm, S. Loi, J. Douglas, S. Michiels, H. Joensuu, M. Fan, D. Lee, J. Ye, K. Byun, J. Kim, S. Xu, Z. Ji, F. Xie, J. Kuang, X. Chen, L. Chen, A. Tsakiroglou, R. Byers, M. Fergie, V. Ramanathan, A. Martel, A. Shephard, S. Ahmed Raza, M. Jahanifar, N. Rajpoot, S. Cho, D. Kim, H. Jang, C. Park, K. Kim, R. Donders, S. Maurits, M. Groeneveld, A. Mickan, J. Meakin, B. van Ginneken, R. Salgado, J. van der Laak and F. Ciompi, "Tumor-infiltrating lymphocytes in breast cancer through artificial intelligence: biomarker analysis from the results of the TIGER challenge", medRxiv, 2025.
   Abstract DOI
4. M. D'Amato, J. van der Laak and F. Ciompi, ""No negatives needed": weakly-supervised regression for interpretable tumor detection in whole-slide histopathology images", arXiv:2502.21109, 2025.
   Abstract DOI arXiv
5. I. Slootweg, N. García-De-La-Puente, G. Litjens and S. Dammak, "Self-supervised large-scale kidney abnormality detection in drug safety assessment studies", arXiv:2509.00131, 2025.
   Abstract DOI arXiv

Papers in conference proceedings

1. J. Lefkes, C. Grisi and G. Litjens, "A Balancing Act: Optimizing Classification and Retrieval in Cross-Modal Vision Models", Medical Imaging with Deep Learning, 2025.
   Abstract Url
2. C. Lems, N. Klubíčková, B. Brattoli, T. Lee, S. Kim, V. Besler, P. Fernandez, L. Pons, A. Laurinavicius, J. Drachneris, D. Montezuma, D. Oliveira, S. Vos, M. Balkenhol, J. van Ipenburg, A. Vos, M. Poceviciute, N. Khalili and F. Ciompi, "Towards a multicentric open DigitAL PatHology assIstant beNchmark: Initial Results from the DALPHIN Study", Laboratory Investigation, 2025;105:103609.
   DOI
3. N. Khalili, J. Spronck, F. Ciompi, J. der Van Laak and G. Litjens, "A human-in-the-loop framework for refining deep learning models in pathology segmentation", Medical Imaging 2025: Digital and Computational Pathology, 2025:21.
   DOI
4. J. Lefkes, M. D'Amato, S. Sun, G. Litjens and F. Ciompi, "Large Language Models Automate Diagnostic Conclusions Generation from Microscopic Descriptions in Multiple Cancer Types", Laboratory Investigation, 2025;105:103608.
   DOI

PhD theses

1. E. Markus-Smeets, "Build bridges to break barriers: Using quantitative imaging to understand pancreas tumor biology", PhD thesis, 2025.
   Abstract Url
2. B. Sturm, "On digital and computational pathology - A paradigm shift towards pathology captured in pixels", PhD thesis, 2025.
   Abstract Url
3. J. Linmans, "Uncertainty estimation in digital pathology: Towards applying artificial intelligence in an uncertain clinical world", PhD thesis, 2025.
   Abstract Url
4. H. Pinckaers, "Prognostic modeling for prostate cancer patients using gigapixel-sized images", PhD thesis, 2025.
   Abstract Url
5. T. de Bel, "Computational Pathology for Early Breast Cancer Diagnostics", PhD thesis, 2025.
   Abstract Url