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. Rahman 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. Hernandez Petzsche, M. Müller, B. Menze, J. Kirschke and B. Wiestler, "DeepISLES: a clinically validated ischemic stroke segmentation model from the ISLES'22 challenge",
Nature Communications,
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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.
N. Antonissen, O. Tryfonos, I. Houben, C. Jacobs, M. de Rooij and K. van Leeuwen, "Artificial intelligence in radiology: 173 commercially available products and their scientific evidence",
European Radiology,
2025.
R. Dinnessen, D. Peeters, N. Antonissen, F. Mohamed Hoesein, H. Gietema, E. Scholten, C. Schaefer-Prokop and C. Jacobs, "Performance of a screening-trained DL model for pulmonary nodule malignancy estimation of incidental clinical nodules",
European Radiology,
2025.
A. Snoeckx, M. Silva, H. Prosch, J. Biederer, T. Frauenfelder, F. Gleeson, C. Jacobs, H. Kauczor, A. Parkar, C. Schaefer-Prokop, M. Prokop and M. Revel, "Lung cancer screening with low-dose CT: definition of positive, indeterminate, and negative screen results. A nodule management recommendation from the European Society of Thoracic Imaging",
European Radiology,
2025.
M. Prokop, C. Schaefer-Prokop, C. Jacobs, A. Snoeckx, J. Biederer, T. Frauenfelder, F. Gleeson, H. Kauczor, A. Parkar, R. Vliegenthart, M. Revel, M. Silva and H. Prosch, "Aggressiveness-guided nodule management for lung cancer screening in Europe--justification for follow-up intervals and definition of growth",
European Radiology,
2025.
E. van der Heijden, M. Snoeren and C. Jacobs, "Incidentele longnoduli op CT-scan: wat te doen? [Incidental pulmonary nodules on CT imaging: what to do?]",
Nederlands Tijdschrift voor Geneeskunde,
2025;169:D8431.
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.
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.
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,
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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.
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,
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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.
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,
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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.
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Scientific Reports,
2025;15.
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,
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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,
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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,
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A. Farris, J. van der Laak and D. van Midden, "Artificial intelligence-enhanced interpretation of kidney transplant biopsy: focus on rejection",
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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,
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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,
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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,
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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",
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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",
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N. Billingy, C. Verberkt, I. Bahce, M. Hassing, J. Schoorlemmer, M. Sarioglu, S. Senan, E. Aarntzen, E. Comans, W. Kievit, S. Teerenstra, C. Jacobs, A. Keijser, M. Heuvel, A. Becker-Commissaris and I. Walraven, "Beneficial value of [18F]FDG PET/CT in the follow-up of patients with stage III non-small cell lung cancer (NVALT31-PET study): study protocol of a multicentre randomised controlled trial",
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R. van Herten, I. Lagogiannis, J. Wolterink, S. Bruns, E. Meulendijks, D. Dey, J. de Groot, J. Henriques, R. Planken, S. Saitta and I. Isgum, "World of Forms: Deformable geometric templates for one-shot surface meshing in coronary CT angiography",
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R. Volleberg, T. Luttikholt, R. van der Waerden, P. Cancian, J. van der Zande, X. Gu, J. Mol, T. Roleder, M. Prokop, C. Sánchez, B. van Ginneken, I. Isgum, S. Saitta, J. Thannhauser and N. van Royen, "Artificial intelligence-based identification of thin-cap fibroatheromas and clinical outcomes: the PECTUS-AI study",
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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",
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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,
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L. Cai, A. Pfob, R. Barr, V. Duda, Z. Alwafai, C. Balleyguier, D. Clevert, S. Fastner, C. Gomez, M. Goncalo, I. Gruber, M. Hahn, P. Kapetas, J. Nees, R. Ohlinger, F. Riedel, M. Rutten, A. Stieber, R. Togawa, C. Sidey-Gibbons, M. Tozaki, S. Wojcinski, J. Heil and M. Golatta, "Deep Learning Model for Breast Shear Wave Elastography to Improve Breast Cancer Diagnosis (INSPiRED 006): An International, Multicenter Analysis",
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B. Obreja, J. Bosma, K. Venkadesh, Z. Saghir, M. Prokop and C. Jacobs, "Characterizing the Impact of Training Data on Generalizability: Application in Deep Learning to Estimate Lung Nodule Malignancy Risk",
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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,
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A. Moradi, F. Zerka, J. Bosma, M. Sunoqrot, B. Abrahamsen, D. Yakar, J. Geerdink, H. Huisman, T. Bathen and M. Elschot, "Optimizing Federated Learning Configurations for MRI Prostate Segmentation and Cancer Detection: A Simulation Study",
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M. Revel, J. Biederer, A. Nair, M. Silva, C. Jacobs, A. Snoeckx, M. Prokop, H. Prosch, A. Parkar, T. Frauenfelder and A. Larici, "ESR Essentials: lung cancer screening with low-dose CT--practice recommendations by the European Society of Thoracic Imaging",
European Radiology,
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M. Klontzas, K. Groot Lipman, T. D' Akinci Antonoli, A. Andreychenko, R. Cuocolo, M. Dietzel, S. Gitto, H. Huisman, J. Santinha, F. Vernuccio, J. Visser and M. Huisman, "ESR Essentials: common performance metrics in AI--practice recommendations by the European Society of Medical Imaging Informatics",
European Radiology,
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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",
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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",
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I. Slootweg, N. García-De-La-Puente, G. Litjens and S. Dammak, "Self-supervised large-scale kidney abnormality detection in drug safety assessment studies",
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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",
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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",
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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",
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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,
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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,
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J. Lefkes, C. Grisi and G. Litjens, "A Balancing Act: Optimizing Classification and Retrieval in Cross-Modal Vision Models",
Medical Imaging with Deep Learning,
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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,
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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.
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.
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.
R. Dinnessen, A. Antonissen, D. Peeters, H. Gietema, E. Scholten, C. Schaefer-Prokop and C. Jacobs, "Exploring AI-enabled nodule management for incidentally detected pulmonary nodules on CT.",
Annual Meeting of the European Society of Thoracic Imaging,
2025.
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.