Publications

2024

Papers in international journals

  1. D. Höppener, W. Aswolinskiy, Z. Qian, D. Tellez, P. Nierop, M. Starmans, I. Nagtegaal, M. Doukas, J. de Wilt, D. Grünhagen, J. van der Laak, P. Vermeulen, F. Ciompi and C. Verhoef, "Classifying histopathological growth patterns for resected colorectal liver metastasis with a deep learning analysis", BJS Open, 2024;8.
    Abstract DOI PMID
  2. J. Twilt, A. Saha, J.S. Bosma, B. van Ginneken, A. Bjartell, A. Padhani, D. Bonekamp, G. Villeirs, G. Salomon, G. Giannarini, J. Kalpathy-Cramer, J. Barentsz, K. Maier-Hein, M. Rusu and Rouviè, "Evaluating Biparametric Versus Multiparametric Magnetic Resonance Imaging for Diagnosing Clinically Significant Prostate Cancer: An International, Paired, Noninferiority, Confirmatory Observer Study", European Urology, 2024.
    Abstract DOI PMID
  3. D. Zhong, G. Sidorenkov, C. Jacobs, P. de Jong, H. Gietema, R. Stadhouders, K. Nackaerts, J. Aerts, M. Prokop, H. Groen, G. de Bock, R. Vliegenthart, M. Heuvelmans and S. Atzen, "Lung Nodule Management in Low-Dose CT Screening for Lung Cancer: Lessons from the NELSON Trial", Radiology, 2024;313.
    Abstract DOI PMID
  4. J. van der Graaf, L. Brundel, M. van Hooff, M. de Kleuver, N. Lessmann, B. Maresch, M. Vestering, J. Spermon, B. van Ginneken and M. Rutten, "AI-based lumbar central canal stenosis classification on sagittal MR images is comparable to experienced radiologists using axial images", European Radiology, 2024.
    Abstract DOI PMID
  5. N. Khalili and F. Ciompi, "Scaling data toward pan-cancer foundation models", Trends in Cancer, 2024;10:871-872.
    Abstract DOI PMID
  6. F. Peisen, A. Gerken, A. Hering, I. Dahm, K. Nikolaou, S. Gatidis, T. Eigentler, T. Amaral, J. Moltz and A. Othman, "Can Delta Radiomics Improve the Prediction of Best Overall Response, Progression-Free Survival, and Overall Survival of Melanoma Patients Treated with Immune Checkpoint Inhibitors?", Cancers, 2024;16:2669.
    Abstract DOI PMID
  7. A. Jurgas, M. Wodzinski, M. D'Amato, J. van der Laak, M. Atzori and H. Müller, "Improving quality control of whole slide images by explicit artifact augmentation", Scientific Reports, 2024;14.
    Abstract DOI PMID
  8. C. Roest, D. Yakar, D. Rener Sitar, J.S. Bosma, D. Rouw, S. Fransen, H. Huisman and T. Kwee, "Multimodal AI Combining Clinical and Imaging Inputs Improves Prostate Cancer Detection", Investigative Radiology, 2024.
    Abstract DOI PMID
  9. K. Faryna, L. Tessier, J. Retamero, S. Bonthu, P. Samanta, N. Singhal, S. Kammerer-Jacquet, C. Radulescu, V. Agosti, A. Collin, X. Farre', J. Fontugne, R. Grobholz, A. Hoogland, K. Leite, M. Oktay, A. Polonia, P. Roy, P. Salles, T. van der Kwast, J. van Ipenburg, J. van der Laak and G. Litjens, "Evaluation of AI-based Gleason grading algorithms "in the wild"", Modern Pathology, 2024:100563.
    Abstract DOI PMID
  10. J. An, Y. Wang, Q. Cai, G. Zhao, S. Dooper, G. Litjens and Z. Gao, "Transformer-Based Weakly Supervised Learning for Whole Slide Lung Cancer Image Classification", IEEE Journal of Biomedical and Health Informatics, 2024:1-14.
    Abstract DOI PMID
  11. C. de Vente, B. van Ginneken, C. Hoyng, C. Klaver and C. Sánchez, "Uncertainty-aware multiple-instance learning for reliable classification: Application to optical coherence tomography", Medical Image Analysis, 2024;97:103259.
    Abstract DOI PMID
  12. V. Bozgo, C. Roest, I. van Oort, D. Yakar, H. Huisman and M. de Rooij, "Prostate MRI and artificial intelligence during active surveillance: should we jump on the bandwagon?", European Radiology, 2024.
    Abstract DOI PMID
  13. A. Saha, J.S. Bosma, J. Twilt, B. van Ginneken, A. Bjartell, A. Padhani, D. Bonekamp, G. Villeirs, G. Salomon, G. Giannarini, J. Kalpathy-Cramer, J. Barentsz, K. Maier-Hein, M. Rusu, O. Rouviere, R. van den Bergh, V. Panebianco, V. Kasivisvanathan, N. Obuchowski, D. Yakar, M. Elschot, J. Veltman, J. Futterer, C. Noordman, I. Slootweg, C. Roest, S. Fransen, M. Sunoqrot, T. Bathen, D. Rouw, J. Immerzeel, J. Geerdink, C. van Run, M. Groeneveld, J. Meakin, A. Karagoz, A. Bone, A. Routier, A. Marcoux, C. Abi-Nader, C. Li, D. Feng, D. Alis, E. Karaarslan, E. Ahn, F. Nicolas, G. Sonn, I. Bhattacharya, J. Kim, J. Shi, H. Jahanandish, H. An, H. Kan, I. Oksuz, L. Qiao, M. Rohe, M. Yergin, M. Khadra, M. Seker, M. Kartal, N. Debs, R. Fan, S. Saunders, S. Soerensen, S. Moroianu, S. Vesal, Y. Yuan, A. Malakoti-Fard, A. Maciunien, A. Kawashima, A. de de Machadov, A. Moreira, A. Ponsiglione, A. Rappaport, A. Stanzione, A. Ciuvasovas, B. Turkbey, B. de Keyzer, B. Pedersen, B. Eijlers, C. Chen, C. Riccardo, D. Alis, E. Courrech Staal, F. Jaderling, F. Langkilde, G. Aringhieri, G. Brembilla, H. Son, H. Vanderlelij, H. Raat, I. Pikuniene, I. Macova, I. Schoots, I. Caglic, J. Zawaideh, J. Wallstrom, L. Bittencourt, M. Khurram, M. Choi, N. Takahashi, N. Tan, P. Franco, P. Gutierrez, P. Thimansson, P. Hanus, P. Puech, P. Rau, P. de Visschere, R. Guillaume, R. Cuocolo, R. Falcao, R. van Stiphout, R. Girometti, R. Briediene, R. Grigiene, S. Gitau, S. Withey, S. Ghai, T. Penzkofer, T. Barrett, V. Tammisetti, V. Logager, V. Cerny, W. Venderink, Y. Law, Y. Lee, M. de Rooij and H. Huisman, "Artificial intelligence and radiologists in prostate cancer detection on MRI (PI-CAI): an international, paired, non-inferiority, confirmatory study", The Lancet Oncology, 2024;25(7):879-887.
    Abstract DOI PMID
  14. E. Smeets, M. Trajkovic-Arsic, D. Geijs, S. Karakaya, M. van Zanten, L. Brosens, B. Feuerecker, M. Gotthardt, J. Siveke, R. Braren, F. Ciompi and E. Aarntzen, "Histology-Based Radiomics for [18F]FDG PET Identifies Tissue Heterogeneity in Pancreatic Cancer", Journal of Nuclear Medicine, 2024:jnumed.123.266262.
    Abstract DOI PMID
  15. P. Vendittelli, J. Bokhorst, E. Smeets, V. Kryklyva, L. Brosens, C. Verbeke and G. Litjens, "Automatic quantification of tumor-stroma ratio as a prognostic marker for pancreatic cancer", PLOS ONE, 2024;19:e0301969.
    Abstract DOI PMID
  16. S. Schalekamp, K. van Leeuwen, E. Calli, K. Murphy, M. Rutten, B. Geurts, L. Peters-Bax, B. van Ginneken and M. Prokop, "Performance of AI to exclude normal chest radiographs to reduce radiologists' workload", European Radiology, 2024.
    Abstract DOI PMID
  17. Q. van Lohuizen, C. Roest, F. Simonis, S. Fransen, T. Kwee, D. Yakar and H. Huisman, "Assessing deep learning reconstruction for faster prostate MRI: visual vs. diagnostic performance metrics", European Radiology, 2024.
    Abstract DOI PMID
  18. A. Scott, M. Limbada, T. Perumal, S. Jaumdally, A. Kotze, C. van der Merwe, M. Cheeba, D. Milimo, K. Murphy, B. van Ginneken, M. de Kock, R. Warren, P. Gina, J. Swanepoel, L. Kühn, S. Oelofse, A. Pooran, A. Esmail, H. Ayles and K. Dheda, "Integrating molecular and radiological screening tools during community-based active case-finding for tuberculosis and COVID-19 in southern Africa", International Journal of Infectious Diseases, 2024:107081.
    Abstract DOI PMID
  19. S. Fransen, C. Roest, Q. Van Lohuizen, J.S. Bosma, F. Simonis, T. Kwee, D. Yakar and H. Huisman, "Using deep learning to optimize the prostate MRI protocol by assessing the diagnostic efficacy of MRI sequences", European Journal of Radiology, 2024;175:111470.
    Abstract DOI PMID
  20. N. Hendrix, W. Hendrix, B. Maresch, J. van Amersfoort, T. Oosterveld-Bonsma, S. Kolderman, M. Vestering, S. Zielinski, K. Rutten, J. Dammeier, L. Ong, B. van Ginneken and M. Rutten, "Artificial intelligence for automated detection and measurements of carpal instability signs on conventional radiographs", European Radiology, 2024.
    Abstract DOI PMID
  21. R. Leon-Ferre, J. Carter, D. Zahrieh, J. Sinnwell, R. Salgado, V. Suman, D. Hillman, J. Boughey, K. Kalari, F. Couch, J. Ingle, M. Balkenhol, F. Ciompi, J. van der Laak and M. Goetz, "Automated mitotic spindle hotspot counts are highly associated with clinical outcomes in systemically untreated early-stage triple-negative breast cancer", npj Breast Cancer, 2024;10.
    Abstract DOI PMID
  22. D. Peeters, N. Alves, K. Venkadesh, R. Dinnessen, Z. Saghir, E. Scholten, C. Schaefer-Prokop, R. Vliegenthart, M. Prokop and C. Jacobs, "Enhancing a deep learning model for pulmonary nodule malignancy risk estimation in chest CT with uncertainty estimation", European Radiology, 2024.
    Abstract DOI PMID
  23. N. van Nistelrooij, K. Ghoul, T. Xi, A. Saha, S. Kempers, M. Cenci, B. Loomans, T. Flügge, B. van Ginneken and S. Vinayahalingam, "Combining public datasets for automated tooth assessment in panoramic radiographs", BMC Oral Health, 2024;24.
    Abstract DOI PMID
  24. V. Eekelen, Leander, J. Spronck, M. Looijen-Salamon, S. Vos, E. Munari, I. Girolami, A. Eccher, B. Acs, C. Boyaci, G. de Souza, M. Demirel-Andishmand, L. Meesters, D. Zegers, L. van der Woude, W. Theelen, M. van den Heuvel, K. Grünberg, B. van Ginneken, J. van der Laak and F. Ciompi, "Comparing deep learning and pathologist quantification of cell-level PD-L1 expression in non-small cell lung cancer whole-slide images", Scientific Reports, 2024;14.
    Abstract DOI PMID
  25. E. Sogancioglu, B. van Ginneken, F. Behrendt, M. Bengs, A. Schlaefer, M. Radu, D. Xu, K. Sheng, F. Scalzo, E. Marcus, S. Papa, J. Teuwen, E. Scholten, S. Schalekamp, N. Hendrix, C. Jacobs, W. Hendrix, C. Sánchez and K. Murphy, "Nodule detection and generation on chest X-rays: NODE21 Challenge", IEEE Transactions on Medical Imaging, 2024;43(8):2839-2853.
    Abstract DOI PMID
  26. U. Mahmood, A. Shukla-Dave, H. Chan, K. Drukker, R. Samala, Q. Chen, D. Vergara, H. Greenspan, N. Petrick, B. Sahiner, Z. Huo, R. Summers, K. Cha, G. Tourassi, T. Deserno, K. Grizzard, J. Näppi, H. Yoshida, D. Regge, R. Mazurchuk, K. Suzuki, L. Morra, H. Huisman, S. Armato and L. Hadjiiski, "Artificial intelligence in medicine: mitigating risks and maximizing benefits via quality assurance, quality control, and acceptance testing", BJR|Artificial Intelligence, 2024;1.
    Abstract DOI PMID
  27. J. van der Graaf, M. van Hooff, C. Buckens, M. Rutten, J. van Susante, R. Kroeze, M. de Kleuver, B. van Ginneken and N. Lessmann, "Lumbar spine segmentation in MR images: a dataset and a public benchmark", Scientific Data, 2024;11(1):264.
    Abstract DOI PMID Cited by ~5
  28. J. van der Graaf, M. van Hooff, B. van Ginneken, M. Huisman, M. Rutten, D. Lamers, N. Lessmann and M. de Kleuver, "Development and validation of AI-based automatic measurement of coronal Cobb angles in degenerative scoliosis using sagittal lumbar MRI", European Radiology, 2024:1-10.
    Abstract DOI PMID
  29. A. Vos, L. Pijnenborg, S. van Vliet, L. Kodach, F. Ciompi, R. van der Post, F. Simmer and I. Nagtegaal, "Biological background of colorectal polyps and carcinomas with heterotopic ossification: A national study and literature review", Human Pathology, 2024;145:34-41.
    Abstract DOI PMID
  30. L. Maier-Hein, A. Reinke, P. Godau, M. Tizabi, F. Buettner, E. Christodoulou, B. Glocker, F. Isensee, J. Kleesiek, M. Kozubek, M. Reyes, M. Riegler, M. Wiesenfarth, A. Kavur, C. Sudre, M. Baumgartner, M. Eisenmann, D. Heckmann-Nötzel, T. Rädsch, L. Acion, M. Antonelli, T. Arbel, S. Bakas, A. Benis, M. Blaschko, M. Cardoso, V. Cheplygina, B. Cimini, G. Collins, K. Farahani, L. Ferrer, A. Galdran, B. van Ginneken, R. Haase, D. Hashimoto, M. Hoffman, M. Huisman, P. Jannin, C. Kahn, D. Kainmueller, B. Kainz, A. Karargyris, A. Karthikesalingam, F. Kofler, A. Kopp-Schneider, A. Kreshuk, T. Kurc, B. Landman, G. Litjens, A. Madani, K. Maier-Hein, A. Martel, P. Mattson, E. Meijering, B. Menze, K. Moons, H. Müller, B. Nichyporuk, F. Nickel, J. Petersen, N. Rajpoot, N. Rieke, J. Saez-Rodriguez, C. Sánchez, S. Shetty, M. van Smeden, R. Summers, A. Taha, A. Tiulpin, S. Tsaftaris, B. Van Calster, G. Varoquaux and P. Jäger, "Metrics reloaded: recommendations for image analysis validation", Nature Methods, 2024;21:195-212.
    Abstract DOI PMID Cited by ~50
  31. A. Reinke, M. Tizabi, M. Baumgartner, M. Eisenmann, D. Heckmann-Nötzel, A. Kavur, T. Rädsch, C. Sudre, L. Acion, M. Antonelli, T. Arbel, S. Bakas, A. Benis, F. Buettner, M. Cardoso, V. Cheplygina, J. Chen, E. Christodoulou, B. Cimini, K. Farahani, L. Ferrer, A. Galdran, B. van Ginneken, B. Glocker, P. Godau, D. Hashimoto, M. Hoffman, M. Huisman, F. Isensee, P. Jannin, C. Kahn, D. Kainmueller, B. Kainz, A. Karargyris, J. Kleesiek, F. Kofler, T. Kooi, A. Kopp-Schneider, M. Kozubek, A. Kreshuk, T. Kurc, B. Landman, G. Litjens, A. Madani, K. Maier-Hein, A. Martel, E. Meijering, B. Menze, K. Moons, H. Müller, B. Nichyporuk, F. Nickel, J. Petersen, S. Rafelski, N. Rajpoot, M. Reyes, M. Riegler, N. Rieke, J. Saez-Rodriguez, C. Sánchez, S. Shetty, R. Summers, A. Taha, A. Tiulpin, S. Tsaftaris, B. Van Calster, G. Varoquaux, Z. Yaniv, P. Jäger and L. Maier-Hein, "Understanding metric-related pitfalls in image analysis validation", Nature Methods, 2024;21:182-194.
    Abstract DOI PMID Cited by ~17
  32. T. Perik, N. Alves, J. Hermans and H. Huisman, "Automated Quantitative Analysis of CT Perfusion to Classify Vascular Phenotypes of Pancreatic Ductal Adenocarcinoma", Cancer, 2024;16(3):577.
    Abstract DOI PMID
  33. L. Boulogne, J. Charbonnier, C. Jacobs, E. van der Heijden and B. van Ginneken, "Estimating lung function from computed tomography at the patient and lobe level using machine learning", Medical Physics, 2024;51:2834-2845.
    Abstract DOI PMID
  34. E. Chelebian, C. Avenel, F. Ciompi and C. Wählby, "DEPICTER: Deep representation clustering for histology annotation", Computers in Biology and Medicine, 2024;170:108026.
    Abstract DOI PMID
  35. B. Russell, K. Beyer, A. Lawlor, M. Roobol, L. Venderbos, S. Remmers, E. Briers, S. MacLennan, S. MacLennan, M. Omar, M. Van Hemelrijck, E. Smith, J. N'Dow, K. Plass, M. Ribal, N. Mottet, R. Shepherd, T. Abbott, K. Mastris, L. Moris, M. Lardas, T. den Van Broeck, P. Willemse, N. Fossati, K. Pang, R. Campi, I. Greco, M. Gacci, S. Serni, A. Bjartell, R. Lonnerbro, A. Briganti, D. Crosti, R. Garzonio, G. Gandaglia, M. Faticoni, G. office, C. Bangma, M. Jongerden, D. Tilki, A. Auvinen, T. Murtola, T. Visakorpi, K. Talala, T. Tammela, A. Siltari, S. Lejeune, L. Colette, S. Caputova, D. Poli, S. Byrne, L. Fialho, A. Rowland, N. Tapela, N. Di Flora, K. Apostolidis, V. Lemair, B. De Meulder, C. Auffray, N. Taibi, A. Hijazy, A. Saporta, K. Sun, S. Power, N. Zounemat Kermani, K. van Bochove, A. Tafreshiha, C. Bernini, D. Horgan, L. Fullwood, M. Holtorf, D. Lancet, G. Bernstein, S. Tripathee, M. Wirth, M. Froehner, B. Brenner, A. Borkowetz, C. Thomas, F. Horn, K. Reiche, M. Kreuz, A. Josefsson, D. Gasi Tandefelt, J. Hugosson, J. Schalken, H. Huisman, T. Hofmarcher, P. Lindgren, E. Andersson, A. Fridhammar, M. Tames Grijalva, S. Evans-Axelsson, F. Verholen, J. Zong, J. Butler-Ransohoff, T. Williamson, R. Waldeck, A. Bruno, E. Nevedomskaya, S. Fatoba, N. Constantinovici, C. Steinbeisser, M. Maass, P. Torremante, E. Dochy, F. Pisa, M. Voss, K. Papineni, J. Wang-silvanto, R. Snijder, X. Wang, M. Lambrecht, R. Wolfinger, S. Eid, S. Palanisamy, S. Haque, L. Antoni, A. Servan, K. Pascoe, P. Robinson, J. Lencart, B. Jaton, H. Turunen, O. Kilkku, P. Pohjanjousi, O. Voima, L. Nevalaita, K. Punakivi, S. Seager, S. Ratwani, K. Grzeslak, J. Brash, E. Longden-Chapman, D. Burke, M. Licour, S. Payne, A. Yong, F. Lujan, S. Le Mare, J. Hendrich, M. Bussmann, Juckeland, Kotik, D. Poli and C. Reich, "Survivorship Data in Prostate Cancer: Where Are We and Where Do We Need To Be?", European Urology Open Science, 2024;59:27-29.
    Abstract DOI PMID
  36. C. Jacobs, "Decoding pulmonary nodules: can machine learning enhance malignancy risk stratification?", Thorax, 2024;79:293-294.
    Abstract DOI PMID
  37. K. Faryna, J. van der Laak and G. Litjens, "Automatic data augmentation to improve generalization of deep learning in H&E stained histopathology", Computers in Biology and Medicine, 2024;170:108018.
    Abstract DOI PMID
  38. D. Schouten, J. van der Laak, B. van Ginneken and G. Litjens, "Full resolution reconstruction of whole-mount sections from digitized individual tissue fragments", Scientific Reports, 2024;14.
    Abstract DOI PMID
  39. C. Jahangir, D. Page, G. Broeckx, C. Gonzalez, C. Burke, C. Murphy, J. Reis-Filho, A. Ly, P. Harms, R. Gupta, M. Vieth, A. Hida, M. Kahila, Z. Kos, P. van Diest, S. Verbandt, J. Thagaard, R. Khiroya, K. Abduljabbar, G. Acosta Haab, B. Acs, S. Adams, J. Almeida, I. Alvarado-Cabrero, F. Azmoudeh-Ardalan, S. Badve, N. Baharun, E. Bellolio, V. Bheemaraju, K. Blenman, L. Mendonça Botinelly Fujimoto, O. Burgues, A. Chardas, M. Cheang, F. Ciompi, L. Cooper, A. Coosemans, G. Corredor, F. Dantas Portela, F. Deman, S. Demaria, S. Dudgeon, M. Elghazawy, C. Fernandez-Martín, S. Fineberg, S. Fox, J. Giltnane, S. Gnjatic, P. Gonzalez-Ericsson, A. Grigoriadis, N. Halama, M. Hanna, A. Harbhajanka, S. Hart, J. Hartman, S. Hewitt, H. Horlings, Z. Husain, S. Irshad, E. Janssen, T. Kataoka, K. Kawaguchi, A. Khramtsov, U. Kiraz, P. Kirtani, L. Kodach, K. Korski, G. Akturk, E. Scott, A. Kovács, A. L\aenkholm , C. Lang-Schwarz, D. Larsimont, J. Lennerz, M. Lerousseau, X. Li, A. Madabhushi, S. Maley, V. Manur Narasimhamurthy, D. Marks, E. McDonald, R. Mehrotra, S. Michiels, D. Kharidehal, F. Minhas, S. Mittal, D. Moore, S. Mushtaq, H. Nighat, T. Papathomas, F. Penault-Llorca, R. Perera, C. Pinard, J. Pinto-Cardenas, G. Pruneri, L. Pusztai, N. Rajpoot, B. Rapoport, T. Rau, J. Ribeiro, D. Rimm, A. Vincent-Salomon, J. Saltz, S. Sayed, E. Hytopoulos, S. Mahon, K. Siziopikou, C. Sotiriou, A. Stenzinger, M. Sughayer, D. Sur, F. Symmans, S. Tanaka, T. Taxter, S. Tejpar, J. Teuwen, E. Thompson, T. Tramm, W. Tran, J. van der Laak, G. Verghese, G. Viale, N. Wahab, T. Walter, Y. Waumans, H. Wen, W. Yang, Y. Yuan, J. Bartlett, S. Loibl, C. Denkert, P. Savas, S. Loi, E. Specht Stovgaard, R. Salgado, W. Gallagher and A. Rahman, "Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer", The Journal of Pathology, 2024;262:271-288.
    Abstract DOI PMID
  40. J. Linmans, G. Raya, J. van der Laak and G. Litjens, "Diffusion models for out-of-distribution detection in digital pathology", Medical Image Analysis, 2024;93:103088.
    Abstract DOI PMID Cited by ~4
  41. D. Geijs, S. Dooper, W. Aswolinskiy, L. Hillen, A. Amir and G. Litjens, "Detection and subtyping of basal cell carcinoma in whole-slide histopathology using weakly-supervised learning", Medical Image Analysis, 2024;93:103063.
    Abstract DOI PMID
  42. K. van Leeuwen, S. Schalekamp, M. Rutten, M. Huisman, C. Schaefer-Prokop, M. de Rooij, B. van Ginneken, B. Maresch, B. Geurts, C. van Dijke, E. Laupman-Koedam, E. Hulleman, E. Verhoeff, E. Meys, F. Mohamed Hoesein, F. ter Brugge, F. van Hoorn, F. van der Wel, I. van den Berk, J. Luyendijk, J. Meakin, J. Habets, J. Verbeke, J. Nederend, K. Meys, L. Deden, L. Langezaal, M. Nasrollah, M. Meij, M. Boomsma, M. Vermeulen, M. Vestering, O. Vijlbrief, P. Algra, S. Algra, S. Bollen, T. Samson, Y. von Brucken Fock, B. Maresch, B. Geurts, C. van Dijke, E. Laupman-Koedam, E. Hulleman, E. Verhoeff, E. Meys, F. Mohamed Hoesein, F. ter Brugge, F. van Hoorn, F. van der Wel, I. van den Berk, J. Luyendijk, J. Meakin, J. Habets, J. Verbeke, J. Nederend, K. Meys, L. Deden, L. Langezaal, M. Nasrollah, M. Meij, M. Boomsma, M. Vermeulen, M. Vestering, O. Vijlbrief, P. Algra, S. Algra, S. Bollen, T. Samson, Y. von Brucken Fock and F. the Group, "Comparison of Commercial AI Software Performance for Radiograph Lung Nodule Detection and Bone Age Prediction", Radiology, 2024;310.
    Abstract DOI PMID Cited by ~3
  43. M. van Rijthoven, S. Obahor, F. Pagliarulo, V. den Maries, P. Schraml, H. Moch, J. van der Laak, F. Ciompi and K. Silina, "Multi-resolution deep learning characterizes tertiary lymphoid structures and their prognostic relevance in solid tumors", Communications Medicine, 2024.
    Abstract DOI PMID Code Algorithm Cited by ~1
  44. S. Vermorgen, T. Gelton, P. Bult, H. Kusters-Vandevelde, J. Hausnerová, K. de Van Vijver, B. Davidson, I. Stefansson, L. Kooreman, A. Qerimi, J. Huvila, B. Gilks, M. Shahi, S. Zomer, C. Bartosch, J. Pijnenborg, J. Bulten, F. Ciompi and M. Simons, "Endometrial Pipelle Biopsy Computer-Aided Diagnosis: A Feasibility Study", Modern Pathology, 2024;37:100417.
    Abstract DOI PMID
  45. G. Solé-Guardia, M. Luijten, B. Geenen, J. Claassen, G. Litjens, F. de Leeuw, M. Wiesmann and A. Kiliaan, "Three-dimensional identification of microvascular pathology and neurovascular inflammation in severe white matter hyperintensity: a case report", Scientific Reports, 2024;14.
    Abstract DOI
  46. N. van Nistelrooij, E. Chaves, M. Cenci, L. Cao, B. Loomans, T. Xi, K. El-Ghoul, V. Romero, G. Lima, T. Flügge, B. van Ginneken, M. Huysmans, S. Vinayahalingam and F. Mendes, "Deep learning-based algorithm for staging secondary caries in bitewings", Caries Research, 2024:1-21.
    Abstract DOI
  47. N. Marini, S. Marchesin, M. Wodzinski, A. Caputo, D. Podareanu, B. Guevara, S. Boytcheva, S. Vatrano, F. Fraggetta, F. Ciompi, G. Silvello, H. Müller and M. Atzori, "Multimodal representations of biomedical knowledge from limited training whole slide images and reports using deep learning", Medical Image Analysis, 2024;97:103303.
    Abstract DOI
  48. W. Xie, C. Jacobs, J. Charbonnier and B. van Ginneken, "Structure and position-aware graph neural network for airway labeling", Medical Image Analysis, 2024;97:103286.
    Abstract DOI Cited by ~5
  49. G. Solé-Guardia, M. Luijten, E. Janssen, R. Visch, B. Geenen, B. Küsters, J. Claassen, G. Litjens, F. de Leeuw, M. Wiesmann and A. Kiliaan, "Deep learning-based segmentation in MRI-(immuno)histological examination of myelin and axonal damage in normal-appearing white matter and white matter hyperintensities", Brain Pathology, 2024.
    Abstract DOI
  50. F. Khoraminia, F. de Jong, F. Akram, G. Litjens, M. Jansen, A. Gonzalez, D. Lichtenburg, A. Stubbs, N. Khalili and T. Zuiverloon, "Abstract B004: Deep learning unveils molecular footprints in histology: predicting molecular subtypes from bladder cancer histology slides", Clinical Cancer Research, 2024;30:B004-B004.
    Abstract DOI
  51. C. Ferreira, K. Venkadesh, C. Jacobs, M. Coimbra and A. Campilho, "Towards automatic forecasting of lung nodule diameter with tabular data and CT imaging", Biomedical Signal Processing and Control, 2024;96:106625.
    Abstract DOI
  52. A. Hering, M. Westphal, A. Gerken, H. Almansour, M. Maurer, B. Geisler, T. Kohlbrandt, T. Eigentler, T. Amaral, N. Lessmann, S. Gatidis, H. Hahn, K. Nikolaou, A. Othman, J. Moltz and F. Peisen, "Improving assessment of lesions in longitudinal CT scans: a bi-institutional reader study on an AI-assisted registration and volumetric segmentation workflow", International Journal of Computer Assisted Radiology and Surgery, 2024.
    Abstract DOI
  53. A. Pfob, T. He, L. Cai, R. Barr, V. Duda, Z. Alwafai, C. Balleyguier, D. Clevert, S. Fastner, C. Gomez, M. Goncalo, I. Gruber, M. Hahn, A. Hennigs, P. Kapetas, S. Lu, J. Nees, R. Ohlinger, F. Riedel, M. Rutten, B. Schaefgen, A. Stieber, R. Togawa, M. Tozaki, S. Wojcinski, C. Xu, G. Rauch, J. Heil, C. Sidey-Gibbons and M. Golatta, "Abstract PO3-07-02: Radiomics Models for B-mode Breast Ultrasound and Strain Elastography to improve Breast Cancer Diagnosis (INSPiRED 005): An International, Multicenter Analysis", Cancer Research, 2024;84:PO3-07-02-PO3-07-02.
    Abstract DOI
  54. S. Bosman, I. Ayakaka, J. Muhairwe, M. Kamele, A. van Heerden, T. Madonsela, N. Labhardt, G. Sommer, J. Bremerich, T. Zoller, K. Murphy, B. van Ginneken, A. Keter, B. Jacobs, M. Bresser, A. Signorell, T. Glass, L. Lynen and K. Reither, "Evaluation of C-Reactive Protein and Computer-Aided Analysis of Chest X-rays as Tuberculosis Triage Tests at Health Facilities in Lesotho and South Africa", Clinical Infectious Diseases, 2024.
    Abstract DOI
  55. M. Ilié, V. Lake, E. de Alava, S. Bonin, S. Chlebowski, A. Delort, E. Dequeker, R. Al-Dieri, A. Diepstra, O. Carpén, C. Eloy, A. Fassina, F. Fend, P. Fernandez, G. Gorkiewicz, S. Heeke, R. Henrique, G. Hoefler, P. Huertas, M. Hummel, K. Kashofer, J. van der Laak, R. de Pablos, F. Schmitt, E. Schuuring, G. Stanta, W. Timens, B. Westphalen and P. Hofman, "Standardization through education of molecular pathology: a spotlight on the European Masters in Molecular Pathology", Virchows Archiv, 2024;485:761-775.
    Abstract DOI
  56. R. Samala, K. Drukker, A. Shukla-Dave, H. Chan, B. Sahiner, N. Petrick, H. Greenspan, U. Mahmood, R. Summers, G. Tourassi, T. Deserno, D. Regge, J. Näppi, H. Yoshida, Z. Huo, Q. Chen, D. Vergara, K. Cha, R. Mazurchuk, K. Grizzard, H. Huisman, L. Morra, K. Suzuki, S. Armato and L. Hadjiiski, "AI and machine learning in medical imaging: key points from development to translation", BJR|Artificial Intelligence, 2024;1.
    Abstract DOI

Preprints

  1. A. Hering, S. de Boer, A. Saha, J. Twilt, D. Yakar, M. de Rooij, H. Huisman and J.S. Bosma, "Deformable MRI Sequence Registration for AI-based Prostate Cancer Diagnosis", arXiv:2404.09666, 2024.
    Abstract DOI arXiv
  2. H. Bran, F. Navarro, I. Ezhov, A. Bayat, D. Das, F. Kofler, S. Shit, D. Waldmannstetter, J. Paetzold, X. Hu, B. Wiestler, L. Zimmer, T. Amiranashvili, C. Prabhakar, C. Berger, J. Weidner, M. Alonso-Basant, A. Rashid, U. Baid, W. Adel, D. Ali, B. Baheti, Y. Bai, I. Bhatt, S. Cetindag, W. Chen, L. Cheng, P. Dutand, L. Dular, M. Elattar, M. Feng, S. Gao, H. Huisman, W. Hu, S. Innani, W. Jiat, D. Karimi, H. Kuijf, J. Kwak, H. Le, X. Lia, H. Lin, T. Liu, J. Ma, K. Ma, T. Ma, I. Oksuz, R. Holland, A. Oliveira, J. Pal, X. Pei, M. Qiao, A. Saha, R. Selvan, L. Shen, J. Silva, Z. Spiclin, S. Talbar, D. Wang, W. Wang, X. Wang, Y. Wang, R. Xia, K. Xu, Y. Yan, M. Yergin, S. Yu, L. Zeng, Y. Zhang, J. Zhao, Y. Zheng, M. Zukovec, R. Do, A. Becker, A. Simpson, E. Konukoglu, A. Jakab, S. Bakas, L. Joskowicz and B. Menze, "QUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge", arXiv:2405.18435, 2024.
    Abstract DOI arXiv
  3. N. Khalili, J. Spronck, F. Ciompi, J. van der Laak and G. Litjens, "Uncertainty-guided annotation enhances segmentation with the human-in-the-loop", arXiv:2404.07208, 2024.
    Abstract DOI arXiv
  4. C. Grisi, G. Litjens and J. van der Laak, "Masked Attention as a Mechanism for Improving Interpretability of Vision Transformers", arXiv:2404.18152, 2024.
    Abstract DOI arXiv
  5. H. Häntze, L. Xu, L. Donle, F. Dorfner, A. Hering, L. Adams and K. Bressem, "Improve Cross-Modality Segmentation by Treating MRI Images as Inverted CT Scans", arXiv:2405.03713, 2024.
    Abstract DOI arXiv
  6. E. de la Rosa, M. Reyes, S. Liew, A. Hutton, R. Wiest, J. Kaesmacher, U. Hanning, A. Hakim, R. Zubal, W. Valenzuela, D. Robben, D. Sima, V. Anania, A. Brys, J. Meakin, A. Mickan, G. Broocks, C. Heitkamp, S. Gao, K. Liang, Z. Zhang, M. Siddiquee, A. Myronenko, P. Ashtari, S. Van Huffel, H. Jeong, C. Yoon, C. Kim, J. Huo, S. Ourselin, R. Sparks, A. Clèrigues, A. Oliver, X. Lladó, L. Chalcroft, I. Pappas, J. Bertels, E. Heylen, J. Moreau, N. Hatami, C. Frindel, A. Qayyum, M. Mazher, D. Puig, S. Lin, C. Juan, T. Hu, L. Boone, M. Goubran, Y. Liu, S. Wegener, F. Kofler, I. Ezhov, S. Shit, M. Petzsche, B. Menze, J. Kirschke and B. Wiestler, "A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge", arXiv:2403.19425, 2024.
    Abstract DOI arXiv
  7. K. Silina and F. Ciompi, "Hitchhiker's guide to cancer-associated lymphoid aggregates in histology images: manual and deep learning-based quantification approaches", arXiv:2403.04142, 2024.
    Abstract DOI arXiv
  8. H. Häntze, L. Xu, F. Dorfner, L. Donle, D. Truhn, H. Aerts, M. Prokop, B. van Ginneken, A. Hering, L. Adams and K. Bressem, "MRSegmentator: Robust Multi-Modality Segmentation of 40 Classes in MRI and CT Sequences", arXiv:2405.06463, 2024.
    Abstract DOI arXiv

Papers in conference proceedings

  1. C. Lems, D. Geijs, J. Bokhorst, M. Sülter, L. van Eekelen and F. Ciompi, "Color Deconvolution for Color-Agnostic and Cross-Modality Analysis of Immunohistochemistry Whole-Slide Images with Deep Learning", 2024 IEEE International Symposium on Biomedical Imaging (ISBI), 2024:1-4.
    Abstract DOI
  2. A. Moradi, F. Zerka, J. Sander Bosma, D. Yakar, J. Geerdink, H. Huisman, T. Frost Bathen and M. Elschot, "Federated learning for prostate cancer detection in biparametric MRI: optimization of rounds, epochs, and aggregation strategy", Medical Imaging 2024: Computer-Aided Diagnosis, 2024.
    Abstract DOI
  3. K. Faryna, J. van der Laak and G. Litjens, "Towards embedding stain-invariance in convolutional neural networks for H&E-stained histopathology", Medical Imaging 2024: Digital and Computational Pathology, 2024.
    Abstract DOI
  4. C. Tommasino, C. Russo, A. Rinaldi and F. Ciompi, ""HoVer-UNet": Accelerating Hovernet with Unet-Based Multi-Class Nuclei Segmentation Via Knowledge Distillation", 2024 IEEE International Symposium on Biomedical Imaging (ISBI), 2024:1-4.
    Abstract DOI
  5. S. Püttmann, L. Borras Ferris, N. Marini, W. Aswolinsky, S. Vatrano, F. Fragetta, I. Nagtegaal, C. van der Post, F. Ciompi, M. Atzori, C. Friedrich and H. Müller, "Automated classification of celiac disease in histopathological images: a multi-scale approach", Medical Imaging 2024: Computer-Aided Diagnosis, 2024.
    Abstract DOI
  6. L. Borras Ferris, S. Püttmann, N. Marini, S. Vatrano, F. Fragetta, A. Caputo, F. Ciompi, M. Atzori and H. Müller, "A full pipeline to analyze lung histopathology images", Medical Imaging 2024: Digital and Computational Pathology, 2024.
    Abstract DOI
  7. N. Contreras, C. Grisi, W. Aswolinskiy, S. Vatrano, F. Fraggetta, I. Nagtegaal, M. D'Amato and F. Ciompi, "Benchmarking Hierarchical Image Pyramid Transformer for the Classification of Colon Biopsies and Polyps Histopathology Images", 2024 IEEE International Symposium on Biomedical Imaging (ISBI), 2024:1-4.
    Abstract DOI

Abstracts

  1. N. Antonissen, K. Venkadesh, H. Gietema, R. Vliegenthart, Z. Saghir, E. Scholten, M. Prokop, C. Schaefer-Prokop and C. Jacobs, "Retrospective validation and comparison of deep learning based risk thresholds versus growth-centric protocols in pulmonary nodule assessment in screening", Annual Meeting of the European Society of Thoracic Imaging, 2024.
    Abstract
  2. B. Sturm, P. Lock, J. Westerga, W. Blokx and J. van der Laak, "Deep learning predicts the effect of neo-adjuvant chemotherapy for patients with triple negative breast cancer", European Congress on Digital Pathology, 2024.
    Abstract
  3. L. Tessier, C. Gonzalez-Gonzalo, D. Tellez, W. Bulten and M. van der Laak, "Large-scale validation of AI-assisted mitosis counting in breast cancer", European Congress on Digital Pathology, 2024.
    Abstract
  4. B. Obreja, K. Venkadesh, W. Hendrix, Z. Saghir, M. Prokop and C. Jacobs, "Deep Learning for estimating pulmonary nodule malignancy risk: How much data does AI need to reach radiologist level performance?", European Congress of Radiology, 2024.
    Abstract
  5. M. Stegeman, G. Bogina, E. Munari, J. van der Laak and F. Ciompi, "Vision Language Foundation Models for Scoring Tumor-Infiltrating Lymphocytes in Breast Cancer through Text Prompting", European Congress on Digital Pathology, 2024.
    Abstract
  6. D. Schouten, N. Khalili, J. van der Laak and G. Litjens, "Full Resolution Three-Dimensional Reconstruction of Non-Serial Prostate Whole-Mounts: Pilot Validation and Initial Results", European Congress on Digital Pathology, 2024.
    Abstract
  7. F. van der Graaf, N. Antonissen, E. Scholten, M. Prokop and C. Jacobs, "Assessing the agreement between privacy-preserving Llama model and human experts when labelling radiology reports for specific significant incidental findings in lung cancer screening", Annual Meeting of the European Society of Thoracic Imaging, 2024.
    Abstract
  8. A. Polejowska, F. Ayatollahi, A. Erdogan, F. Ciompi and A. Boleij, "Spirochetosis detection in colon histopathology images via fine-tuning and boosting techniques using foundation models", Medical Imaging with Deep Learning 2024, 2024.
    Abstract
  9. L. Eekelen, G. den Heuvel, L. Studer, J. Spronck, K. Grünberg, D. Zegers, J. der Laak, M. den Heuvel and F. Ciompi, "Immunotherapy response prediction for non-small cell lung cancer is improved by using cell-graphs of the tumor microenvironment", European Congress on Digital Pathology, 2024.
    Abstract
  10. M. D'Amato, A. Boden, P. van Diest, N. Stathonikos, H. Hoefling, F. Versaevel, G. Litjens, F. Ciompi and J. van der Laak, "Automated Quality Control in Histopathology through Artifact Segmentation", European Congress on Digital Pathology, 2024.
    Abstract
  11. D. Peeters, K. Venkadesh, R. Dinnessen, Z. Saghir, E. Scholten, R. Vliegenthart, M. Prokop and C. Jacobs, "Towards safe and reliable implementation of AI models for nodule malignancy estimation using distance-based out-of-distribution detection", Annual Meeting of the European Society of Thoracic Imaging, 2024.
    Abstract
  12. M. Vitale, M. Boenink, M. Vegter and C. Jacobs, "Norms for Responsible AI-enabled Population Screening", European Society for Philosophy of Medicine and Healthcare, 2024.
    Abstract
  13. F. van der Graaf, N. Antonissen, Z. Saghir, M. Prokop and C. Jacobs, "External validation of the Sybil risk model as a tool to identify low-risk individuals eligible for biennial lung cancer screening", European Congress of Radiology, 2024.
    Abstract
  14. D. Midden, L. Studer, M. Hermsen, N. Kozakowski, J. Kers, L. Hilbrands and J. van der Laak, "Deep learning-based segmentation of peritubular capillaries in kidney transplant biopsies.", European Congress on Digital Pathology, 2024.
    Abstract
  15. S. de Jong, M. Groot, R. Verhoeven, E. van der Heijden and F. Ciompi, "Weakly supervised lung cancer detection on label-free intraoperative microscopy with higher harmonic generation", Medical Imaging with Deep Learning 2024, 2024.
    Abstract
  16. D. Midden, L. Studer, M. Hermsen, A. Farris, J. Kers, L. Hilbrands and J. van der Laak, "Introducing the MONKEY Challenge: Machine-learning for Optimal detection of iNflammatory cells in the KidnEY", European Congress on Digital Pathology, 2024.
    Abstract
  17. R. Dinnessen, K. Venkadesh, D. Peeters, H. Gietema, E. Scholten, C. Schaefer-Prokop and C. Jacobs, "External validation of an AI algorithm for pulmonary nodule malignancy risk estimation on a dataset of incidentally detected pulmonary nodules", European Congress of Radiology, 2024.
    Abstract

PhD theses

  1. T. Haddad, "Tumor budding: a dive into the edge of colorectal cancer invasion", PhD thesis, 2024.
    Abstract Url
  2. B. de Wilde, "AI-assisted detection of adhesions on cine-MRI", PhD thesis, 2024.
    Abstract Url
  3. E. Sogancioglu, "Deep Learning for Clinical Practice: Enhancing Chest X-ray Diagnostics", PhD thesis, 2024.
    Abstract Url
  4. N. Hendrix, "Artificial Intelligence for Computer Aided Diagnosis of Scaphoid Fractures and Associated Instability on Conventional Radiography", PhD thesis, 2024.
    Abstract Url
  5. J. Bokhorst, "Hidden in plain sight. Automatic detection of tumor budding in digital pathology images of colorectal cancer", PhD thesis, 2024.
    Abstract Url
  6. G. Humpire-Mamani, "Deep Learning for Localization and Segmentation in Thorax Abdomen CT", PhD thesis, 2024.
    Abstract Url
  7. M. Hosseinzadeh, "Prostate Cancer Detection in MRI using Deep Learning", PhD thesis, 2024.
    Abstract Url
  8. S. van de Leemput, "Efficient neural network training for 4D-CTA stroke imaging", PhD thesis, 2024.
    Abstract Url
  9. W. Hendrix, "Artificial Intelligence for Detection of Lung and Airway Nodules in Clinical Chest CT scans", PhD thesis, 2024.
    Abstract Url
  10. K. Venkadesh, "AI for lung cancer screening", PhD thesis, 2024.
    Abstract Url

Other publications

  1. F. Falta, C. Gro\ssbr öhmer, A. Hering, A. Bigalke and M. Heinrich, "Abstract: Combined 3D Dataset for CT- and Point Cloud-based Intra-patient Lung Registration Lung250M-4B", Bildverarbeitung fur die Medizin 2024, 2024:53-53.
    Abstract DOI
  2. T. Kohlbrandt, J. Moltz, S. Heldmann, A. Hering and J. Lellmann, "Joint Learning of Image Registration and Change Detection for Lung CT Images", Bildverarbeitung fur die Medizin 2024, 2024:46-51.
    Abstract DOI