Publications

2025

Papers in international journals

  1. M. Sappia, C. de Korte, B. van Ginneken, D. Ninalga, S. Kondo, S. Kasai, K. Hirasawa, T. Akumu, C. Martín-Isla, K. Lekadir, V. Campello, J. Fabila, A. Beverdam, J. van Dillen, C. Neff and K. Murphy, "ACOUSLIC-AI challenge report: Fetal abdominal circumference measurement on blind-sweep ultrasound data from low-income countries", Medical Image Analysis, 2025;105:103640.
    Abstract DOI PMID
  2. J. Twilt, A. Saha, J.S. Bosma, A. Padhani, D. Bonekamp, G. Giannarini, R. van den Bergh, V. Kasivisvanathan, N. Obuchowski, D. Yakar, M. Elschot, J. Veltman, J. Fütterer, H. Huisman, M. de Rooij, P. Consortium, J. Twilt, A. Saha, J.S. Bosma, D. Yakar, M. Elschot, J. Veltman, J. Fütterer, M. de Rooij, H. Huisman, A. Bjartell, A. Padhani, D. Bonekamp, G. Villeirs, G. Salomon, G. Giannarini, J. Kalpathy-Cramer, J. Barentsz, K. Maier-Hein, M. Rusu, N. Obuchowski, O. Rouviere, R. van den Bergh, V. Panebianco, V. Kasivisvanathan, A. Malakoti-Fard, A. Dehghanpour, A. Moreira, A. Cazzato, A. Ponsiglione, A. Stanzione, B. de Keyzer, B. Pedersen, C. Page, C. Mai, D. Alis, D. Versteegden, E. Camisassa, E. Staal, F. Martini, F. Alessandrino, F. Jäderling, G. Agrotis, G. Avesani, G. Brembilla, G. Francese, H. Raat, H. Sahin, I. Schoots, I. Caglic, J. Zawaideh, L. Bittencourt, L. Mannacio, M. Gonçalves, M. Özdemir, M. Nahouraii, M. da Silva, M. Khurram, M. Choi, P. Franco, P. Correia, P. Riesenberger, P. Hanus, P. de Visschere, R. Guillaume, R. Cuocolo, R. Falcão, R. van Stiphout, R. Girometti, R. Gabriele, R. Briediene, R. Grigiene, S. Withey, S. Durmaz, S. Santos, T. Russo, T. Barrett, V. Forte, V. Tammisetti, V. Obmann, W. Weston, Y. Law, Y. Yuruk, Y. Chang and Y. Arita, "AI-Assisted vs Unassisted Identification of Prostate Cancer in Magnetic Resonance Images", JAMA Network Open, 2025;8:e2515672.
    Abstract DOI PMID
  3. S. Fransen, J.S. Bosma, Q. van Lohuizen, C. Roest, F. Simonis, T. Kwee, D. Yakar and H. Huisman, "Simulating workload reduction with an AI-based prostate cancer detection pathway using a prediction uncertainty metric", European Radiology, 2025.
    Abstract DOI PMID
  4. C. Noordman, S. Borgers, M. Boomsma, T. Kwee, M. van der Lees, C. Overduin, M. de Rooij, D. Yakar, J. Fütterer and H. Huisman, "Deep learning-based temporal MR image reconstruction for accelerated interventional imaging during in-bore biopsies", Journal of Medical Imaging, 2025;12.
    Abstract DOI PMID
  5. 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
  6. 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.
    Abstract DOI PMID
  7. 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
  8. R. Volleberg, R. van der Waerden, T. Luttikholt, J. van der Zande, P. Cancian, X. Gu, J. Mol, S. Quax, M. Prokop, C. Sánchez, B. van Ginneken, I. Isgum, J. Thannhauser, S. Saitta, K. Nishimiya, T. Roleder and N. van Royen, "Comprehensive full-vessel segmentation and volumetric plaque quantification for intracoronary optical coherence tomography using deep learning", European Heart Journal - Digital Health, 2025;6:404-416.
    Abstract DOI PMID
  9. 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
  10. 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
  11. N. Rodrigues, J. de Almeida, A. Verde, A. Gaivão, C. Bireiro, I. Santiago, J. Ip, S. Belião, C. Matos, L. Vanneschi, M. Tsiknakis, K. Marias, D. Regge, S. Silva, T. Consortium, M. Tsiknakis, K. Marias, S. Sfakianakis, V. Kalokyri, E. Trivizakis, G. Kalliatakis, A. Dimitriadis, D. Fotiadis, N. Tachos, E. Mylona, D. Zaridis, C. Kalantzopoulos, N. Papanikolaou, J. de Almeida, A. Verde, A. Rodrigues, N. Rodrigues, M. Chambel, H. Huisman, M. Rooij, A. Saha, J. Twilt, J. Futterer, L. Martí-Bonmatí, L. Cerdá-Alberich, G. Ribas, S. Navarro, M. Marfil, E. Neri, G. Aringhieri, L. Tumminello, V. Mendola, D. Akata, M. Özmen, A. Karaosmanoglu, F. Atak, M. Karcaaltincaba, J. Vilanova, J. Usinskiene, R. Briediene, A. Untanas, K. Slidevska, K. Vasilis, G. Georgios, D. Koh, R. Emsley, S. Vit, A. Ribeiro, S. Doran, T. Jacobs, G. García-Martí, D. Regge, V. Giannini, S. Mazzetti, G. Cappello, G. Maimone, V. Napolitano, S. Colantonio, M. Pascali, E. Pachetti, G. Corso, D. Germanese, A. Berti, G. Carloni, J. Kalpathy-Cramer, C. Bridge, J. Correia, W. Hernandez, Z. Giavri, C. Pollalis, D. Agraniotis, A. Pastor, J. Mora, C. Saillant, T. Henne, R. Marquez and N. Papanikolaou, "Effective reduction of unnecessary biopsies through a deep-learning-assisted aggressive prostate cancer detector", Scientific Reports, 2025;15.
    Abstract DOI PMID
  12. B. Turkbey, H. Huisman, A. Fedorov, K. Macura, D. Margolis, V. Panebianco, A. Oto, I. Schoots, M. Siddiqui, C. Moore, O. Rouvière, L. Bittencourt, A. Padhani, C. Tempany and M. Haider, "Requirements for AI Development and Reporting for MRI Prostate Cancer Detection in Biopsy-Naive Men: PI-RADS Steering Committee, Version 1.0", Radiology, 2025;315.
    Abstract DOI PMID
  13. T. Luttikholt, J. Thannhauser and N. van Royen, "Detection of large areas of thin-cap fibroatheroma in a recurrent STEMI patient using a novel artificial intelligence algorithm: moving from 2D to 3D", European Heart Journal, 2025.
    Abstract DOI PMID
  14. 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
  15. W. Hendrix, N. Hendrix, E. Scholten, B. van Ginneken, M. Prokop, M. Rutten and C. Jacobs, "Artificial intelligence for the detection of airway nodules in chest CT scans", European Radiology, 2025.
    Abstract DOI PMID
  16. C. Roest, T. Kwee, I. de Jong, I. Schoots, P. van Leeuwen, S. Heijmink, H. van der Poel, S. Fransen, A. Saha, H. Huisman and D. Yakar, "Development and Validation of a Deep Learning Model Based on MRI and Clinical Characteristics to Predict Risk of Prostate Cancer Progression", Radiology: Imaging Cancer, 2025;7.
    Abstract DOI PMID
  17. D. Peeters, K. Venkadesh, R. Dinnessen, Z. Saghir, E. Scholten, R. Vliegenthart, M. Prokop and C. Jacobs, "Towards safe and reliable deep learning for lung nodule malignancy estimation using out-of-distribution detection", Computers in Biology and Medicine, 2025;186:109633.
    Abstract DOI PMID
  18. H. Long, L. Hu, L. Wei, L. Dai, C. Fu, Y. Lu, C. Xu, Z. Hu, L. Wang, Z. Xu, R. Grimm, H. Busch, T. Benkert, A. Kamen, B. Lou, H. Huisman, A. Tong, T. Penzkofer, M. Choi, I. Shabunin, D. Winkel, P. Xing, D. Szolar, F. Coakley, S. Shea, E. Szurowska, W. Zhu and J. Zhao, "Improved prostate cancer diagnosis: upgraded prostate imaging reporting and data system (PI-RADS) scores by zoomed diffusion-weighted imaging enhance deep-learning-based computer-aided diagnosis accuracy", Quantitative Imaging in Medicine and Surgery, 2025;15:2132-2145.
    Abstract DOI
  19. R. van der Waerden, R. Volleberg, T. Luttikholt, P. Cancian, J. van der Zande, G. Stone, N. Holm, E. Kedhi, J. Escaned, D. Pellegrini, G. Guagliumi, S. Mehta, N. Pinilla-Echeverri, R. Moreno, L. Räber, T. Roleder, B. van Ginneken, C. Sánchez, I. Isgum, N. van Royen and J. Thannhauser, "Artificial intelligence for the analysis of intracoronary optical coherence tomography images: a systematic review", European Heart Journal - Digital Health, 2025.
    Abstract DOI
  20. Q. Lohuizen, S. Fransen, G. Yiasemis, C. Roest, F. Simonis, T. Kwee, D. Yakar and H. Huisman, "Deep learning reconstruction for prostate MRI: Impact of field-of-view selection on global and regional image quality", European Journal of Radiology Artificial Intelligence, 2025;2:100017.
    Abstract DOI
  21. L. Thijssen, M. de Rooij and H. Huisman, "External validation of automated prostate MR T2-weighted image quality assessment on multi-centre multi-vendor data", European Journal of Radiology Artificial Intelligence, 2025;1:100002.
    Abstract DOI

Preprints

  1. Y. Wang, T. Chen, S. Vinayahalingam, T. Wu, C. Chang, H. Chang, H. Wei, M. Chen, C. Ko, D. Moin, B. van Ginneken, T. Xi, H. Tsai, M. Chen, T. Hsu and H. Chou, "Artificial Intelligence to Assess Dental Findings from Panoramic Radiographs -- A Multinational Study", arXiv:2502.10277, 2025.
    Abstract DOI arXiv
  2. W. Heyer, Y. Elser, L. Berkel, X. Song, X. Xu, P. Yan, X. Jia, J. Duan, Z. Li, T. Mok, B. LI, C. Staackmann, C. Gro\ssbr öhmer, L. Hansen, A. Hering, M. Sieren and M. Heinrich, "OncoReg: Medical Image Registration for Oncological Challenges", arXiv:2503.23179, 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. 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
  5. 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
  6. 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
  7. J. Chen, S. Wei, J. Honkamaa, P. Marttinen, H. Zhang, M. Liu, Y. Zhou, Z. Tan, Z. Wang, Y. Wang, H. Zhou, S. Hu, Y. Zhang, Q. Tao, L. Förner, T. Wendler, B. Jian, B. Wiestler, T. Hable, J. Kim, D. Ruan, F. Madesta, T. Sentker, W. Heyer, L. Zuo, Y. Dai, J. Wu, J. Prince, H. Bai, Y. Du, Y. Liu, A. Hering, R. Dorent, L. Hansen, M. Heinrich and A. Carass, "Beyond the LUMIR challenge: The pathway to foundational registration models", arXiv:2505.24160, 2025.
    Abstract DOI arXiv

Papers in conference proceedings

  1. C. de Vente, K. Venkadesh, B. van Ginneken and C. S'anchez, "SlicerNNInteractive: A 3D Slicer extension for nnInteractive", 2025.
    Abstract Url
  2. P. Cancian, S. Saitta, X. Gu, R. van Herten, T. Luttikholt, J. Thannhauser, R. Volleberg, R. van der Waerden, J. van der Zande, C. Sánchez, B. van Ginneken, N. van Royen and I. Isgum, "Attenuation artifact detection and severity classification in intracoronary OCT using mixed image representations", Medical Imaging 2025: Image Processing, 2025.
    Abstract DOI
  3. X. Pham, M. Prokop, B. van Ginneken and A. Hering, "Divide to conquer: a field decomposition approach for multi-organ whole-body CT image registration", Medical Imaging 2025: Image Processing, 2025:48.
    Abstract DOI
  4. G. Lozupone, A. Bria, F. Fontanella, F. Meijer, C. Stefano and H. Huisman, "Latent Diffusion Autoencoders: Toward Efficient and Meaningful Unsupervised Representation Learning in Medical Imaging", 2025.
    Abstract DOI
  5. 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.
    Abstract DOI
  6. 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.
    Abstract DOI
  7. 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
  8. A. Jiménez-Sánchez, N. Avlona, S. de Boer, V. Campello, A. Feragen, E. Ferrante, M. Ganz, J. Gichoya, C. González, S. Groefsema, A. Hering, A. Hulman, L. Joskowicz, D. Juodelyte, M. Kandemir, T. Kooi, J. Lérida, L. Li, A. Pacheco, T. Rädsch, M. Reyes, T. Sourget, B. van Ginneken, D. Wen, N. Weng, J. Xu, H. Zając, M. Zuluaga and V. Cheplygina, "In the Picture: Medical Imaging Datasets, Artifacts, and their Living Review", Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency, 2025.
    Abstract DOI
  9. 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.
    Abstract DOI

Abstracts

  1. N. Antonissen, I. Houben, O. Tryfonos, M. De Rooij and K. Van Leeuwen, "Evolution of commercially available artificial intelligence in radiology: a follow-up on peer-reviewed evidence of 179 products", European Congress of Radiology, 2025.
    Abstract
  2. D. Peeters, B. Obreja, N. Antonissen, R. Dinnessen, Z. Saghir, E. Scholten, R. Vliegenthart, M. Prokop and C. Jacobs, "Benchmarking of Artificial Intelligence and Radiologists for Lung Cancer Screening in CT: The LUNA25 Challenge", European Congress of Radiology, 2025.
    Abstract

PhD theses

  1. H. Pinckaers, "Prognostic modeling for prostate cancer patients using gigapixel-sized images", PhD thesis, 2025.
    Abstract Url
  2. L. Boulogne, "Accelerating research on 3D medical image classification and regression", PhD thesis, 2025.
    Abstract Url
  3. E. Markus-Smeets, "Build bridges to break barriers: Using quantitative imaging to understand pancreas tumor biology", PhD thesis, 2025.
    Abstract Url
  4. J. Linmans, "Uncertainty estimation in digital pathology: Towards applying artificial intelligence in an uncertain clinical world", PhD thesis, 2025.
    Abstract Url
  5. J. van der Graaf, "AI-driven MRI analysis for low back pain management", PhD thesis, 2025.
    Abstract Url