Publications

all all years 2026 2025 2024 2023 2022 2021 2020 2019 2018 2017 2016 2015 2014 2013 2012 and before most cited

2026

Papers in international journals

D. Peeters, B. Obreja, N. Antonissen, Z. Saghir, U. Pastorino, M. Silva, G. de Bock, H. Gietema, F. Gleeson, M. Heuvelmans, S. Lam, G. Litjens, F. Mohamed Hoesein, C. Schaefer-Prokop, E. Scholten, A. Snoeckx, E. van der Heijden, R. Vliegenthart, M. Prokop, C. Jacobs and O. behalf of the Consortium, "Benchmarking of AI and Radiologists for Indeterminate Lung Nodule Malignancy Risk Estimation on Screening CT: The LUNA25 Challenge", Radiology: Artificial Intelligence, 2026.
Abstract DOI PMID
N. Antonissen, S. Schalekamp, H. Hahn, K. van Leeuwen and C. Jacobs, "Commercial AI for CT lung cancer screening: product capabilities, coverage of nodule management tasks and supporting evidence", European Radiology, 2026.
Abstract DOI PMID
S. Bunk, E. Bennink, G. Sidorenkov, M. Heuvelmans, H. Groen, H. Gietema, M. Prokop, J. Aerts, C. Jacobs, G. de Bock, P. de Jong, R. Vliegenthart, F. Mohamed Hoesein, J. Aerts, R. Cornelissen, R. Stadhouders, J. van Rooij, L. Trap, M. Prokop, C. Schaefer-Prokop, C. Jacobs, G. de Bock, M. Heuvelmans, G. Sidorenkov, D. Zhong, H. Groen, R. Vliegenthart, P. de Jong, F. Mohamed Hoesein, S. Bunk and G. Downward, "CT-based body composition and its change through time in relation to outcomes in participants screened for lung cancer", eBioMedicine, 2026;127:106276.
DOI PMID
J. Twilt, A. Saha, J.S. Bosma, G. Giannarini, A. Padhani, D. Yakar, M. Elschot, J. Veltman, J. Fütterer, H. Huisman, M. de Rooij, F. the Consortium, A. Saha, J.S. Bosma, J. Twilt, B. van Ginneken, 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, 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, H. Huisman, J. Kalpathy-Cramer, J. Barentsz, K. Maier-Hein, M. Elschot, M. Rusu, N. Obuchowski, O. Rouviere, R. van den Bergh, V. Panebianco, V. Kasivisvanathan, A. Karagöz, A. Bône, 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. Rohé, M. Yergin, M. Rusu, M. Khadra, M. Seker, M. Kartal, N. Debs, R. Fan, S. Saunders, S. Soerensen, S. Moroianu, S. Vesal, Y. Yuan, A. Malakoti-Fard, A. Mačiunien, A. Kawashima, A. 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. Jäderling, F. Langkilde, G. Aringhieri, G. Brembilla, H. Son, H. Vanderlelij, H. Raat, I. Pikuniene, I. Macova, I. Schoots, I. Caglic, J. Zawaideh, J. Wallström, L. Bittencourt, M. Khurram, M. Choi, N. Takahashi, N. Tan, O. Rouvière, P. Franco, P. Gutierrez, P. Thimansson, P. Hanus, P. Puech, P. Rau, P. De Visschere, R. Guillaume, R. Cuocolo, R. Falcão, R. van Stiphout, R. Girometti, R. Briediene, R. Grigiene, S. Gitau, S. Withey, S. Ghai, T. Penzkofer, T. Barrett, V. Panebianco, V. Tammisetti, V. L\ogager , V. Černý, W. Venderink, Y. Law and Y. Lee, "Evaluating an AI-driven Triaging Workflow for MRI-based Clinically Significant Prostate Cancer Diagnosis: A Simulation Study", Radiology: Imaging Cancer, 2026;8.
Abstract DOI PMID
S. Scharm, C. Schaefer-Prokop, A. Schreuder, J. Ehmig, A. Hunkemöller, J. Fuge, B. Seeliger, J. Schupp, F. Wacker and H. Shin, "Extent of alveolar collapse in expiratory CT as a prognostic marker in idiopathic pulmonary fibrosis", PLOS One, 2026;21:e0345308.
Abstract DOI PMID
D. Zhong, G. Sidorenkov, M. Greuter, C. Jacobs, P. de Jong, H. Gietema, H. Groen, F. Mohamed Hoesein, N. Antonissen, R. Stadhouders, H. Lancaster, M. Heuvelmans, R. Vliegenthart and G. de Bock, "Improving Lung Cancer Screening Selection: A Comparative Analysis of Risk Models and Traditional Criteria in a Western European General Population", Cancers, 2026;18:724.
Abstract DOI PMID
F. Wilting, J. Douwes, A. Patel, F. Schreuder, R. Dammers, G. Hannink, W. Jolink, S. Pegge, L. Sondag, M. Wermer, H. van der Worp, F. Meijer and C. Klijn, "Deep learning-based automated segmentation of intracerebral haemorrhage, intraventricular haemorrhage and perihaematomal oedema on non-contrast CT", European Stroke Journal, 2026;11.
Abstract DOI PMID
S. Shojaei, D. Yakar, N. Vellinga, V. Bozgo, T. Kwee, H. Huisman and J. Mifsud Bonnici, "The AI Act and the MDR post-market requirements for semiautonomous AI SaMD: a radiology case study in prostate cancer", Abdominal Radiology, 2026.
Abstract DOI PMID
T. Perik, G. Litjens, N. Alves, E. Smit, M. Stommel, E. van Geenen, H. Huisman and J. Hermans, "Quantitative CT Perfusion as a prognostic biomarker for chemotherapy response in patients with pancreatic ductal adenocarcinoma", Abdominal Radiology, 2026.
Abstract DOI
M. Rijthoven, W. Aswolinskiy, L. Tessier, R. Salgado, J. van der Laak, F. Ciompi and TIGER consortium, "Analysis of computational tumor-infiltrating lymphocytes in breast cancer from the results of the TIGER challenge", Nature Communications, 2026.
Abstract DOI
J. Dixon-Douglas, D. Drubay, R. Salgado, B. Acs, J. van der Laak, Y. Yuan, M. Amgad, L. Cooper, Y. Hagos, K. AbdulJabbar, J. Meakin, B. van Ginneken, H. Yan, J. Lemonnier, F. Penault-Llorca, M. Lacroix-Triki, H. Joensuu, P. Kellokumpu-Lehtinen, S. Loibl, C. Denkert, G. Viale, M. Colleoni, C. Sotiriou, M. Piccart, M. Dieci, S. Demaria, R. Kammler, A. Wolff, J. Sparano, S. Adams, S. Badve, R. Gray, G. Curigliano, A. Salomon, T. Nielsen, L. Pusztai, F. Ciompi, S. Michiels and S. Loi, "Artificial intelligence-based tumour infiltrating lymphocyte quantification in patients with triple-negative breast cancer: an independent validation study", The Lancet Oncology, 2026;27:1181-1192.
DOI
J. van der Zande, L. Alvarez-Florez, R. Volleberg, C. Brás, D. Karkalousos, R. Nijveldt, N. van Royen, T. Leiner, N. Khalili, G. Litjens, J. Thannhauser and I. Isgum, "Deep Learning for Cardiac Image Analysis", JACC: Cardiovascular Imaging, 2026.
DOI
D. Schouten, J. van der Laak, D. Somford, H. Küsters-Vandevelde, N. Khalili and G. Litjens, "Three-dimensional reconstruction of gigapixel whole-mount histopathology specimens with RAPID", Scientific Reports, 2026.
Abstract DOI
E. Munari, P. Antonini, L. Cima, R. Polati, A. Caliò, S. Gobbo, M. Colecchia, G. Netto, A. Antonelli, R. Bertolo, C. Grisi, G. Litjens and M. Brunelli, "The evolution of prostate cancer grading: from Gleason score to risk taxonomy and the artificial intelligence revolution", Virchows Archiv, 2026.
Abstract DOI
F. Khoraminia, M. Olislagers, F. de Jong, F. Akram, A. Nakauma Gonzalez, D. Lichtenberg, A. Stubbs, J. Costello, L. Rijstenberg, G. van Leenders, A. Vrieling, K. Aben, L. Kiemeney, R. Hoedemaeker, C. Bangma, S. Vermeulen, G. Litjens, N. Khalili and T. Zuiverloon, "Predicting bladder cancer molecular subtypes linked to bacillus Calmette-Guerin response from histology images using deep learning", Preprint, 2026.
Abstract DOI
M. Sappia, B. van Ginneken, C. de Korte, J. van Dillen and K. Murphy, "Assessment of modifications to a blind-sweep ultrasound protocol for improved lower-uterus imaging by novice operators", Scientific Reports, 2026.
Abstract DOI
K. Villiamsson, L. Fornstedt, G. Litjens, A. Amir, N. Sjöblom, A. Kaatonen, O. Vesala, F. Yacob, J. Paoli and N. Neittaanmäki, "Detection of basal cell carcinoma on whole-slide images from Mohs micrographic surgery using weakly supervised learning", JAAD International, 2026;28:76-85.
DOI
N. Uysal, C. Grisi, K. Faryna, J. van Ipenburg and G. Litjens, "Towards patient-level Gleason grading from AI-based analysis of individual sections", Scientific Reports, 2026.
Abstract DOI
Q. van Lohuizen, S. Fransen, G. Yiasemis, J. Twilt, C. Roest, Y. Arita, J. Borstlap, J. Fütterer, M. de Rooij, D. Rouw, I. Schoots, B. Turkbey, S. Withey, F. Simonis, H. Huisman, T. Kwee, J. Teuwen and D. Yakar, "Diagnostic assessment of artificial intelligence reconstruction on accelerated prostate MRI: a retrospective, paired, multi-reader multi-case study", European Radiology, 2026.
Abstract DOI
C. van den Berg, J. Dittrich, S. Scharm, C. Schaefer-Prokop, S. Dettmer, A. Hunkemoeller, J. Eckstein, J. Glandorf, F. Wacker, G. Pöhler and H. Shin, "CT-based lung ventilation metrics: reference ranges and pulmonary function test correlations in healthy individuals", European Radiology, 2026.
Abstract DOI
R. Dinnessen, N. Antonissen, D. Peeters, H. Gietema, M. Henkens, F. Mohamed Hoesein, E. Scholten, C. Schaefer-Prokop and C. Jacobs, "Multicentre performance and consistency of two deep learning models for malignancy probability estimation of incidental pulmonary nodules", European Radiology, 2026.
Abstract DOI
G. Querzoli, G. Bogina, M. Marconi, N. Tumino, P. Vacca, L. Righi, S. Pilotto, A. Caliò, L. Cima, S. Gobbo, M. Cecchini, G. Paolino, F. Ciompi, R. Accolla, A. Scarpa, G. Lunardi, E. Marcenaro, L. Moretta, G. Zamboni and E. Munari, "HLA-G expression in non-small cell lung cancer: prognostic significance and interplay with PD-L1 and CD8+ tumor-infiltrating lymphocytes", Frontiers in Immunology, 2026;17.
Abstract DOI
T. Coelho, J.S. Bosma, V. Bozgo, C. Noordman, R. Grimm, M. de Rooij, M. Maas and H. Huisman, "Diagnostically Calibrated AI Image Quality Framework Applied to Prostate Cancer Detection at MRI", Radiology, 2026;320.
Abstract DOI
N. Alves, M. Schuurmans, J. Hermans and H. Huisman, "AI-assisted screening for pancreatic cancer - Authors' reply", The Lancet Oncology, 2026;27:e124.
DOI
K. Dercksen, A. de Vries and B. van Ginneken, "PRESTIGE: Prevalence estimation for interactive guesstimates", Artificial Intelligence in Medicine, 2026;181:103496.
DOI
S. Jarkman, M. Lindvall, C. Lundström, D. Treanor and J. van der Laak, "Designing AI Tools for Pathology: A Mixed-Method Study on User Interface Design for Breast Cancer Lymph Node Metastases Detection", Intelligence-Based Medicine, 2026:100396.
DOI
J. Tagscherer, S. de Boer, F. van der Graaf, L. Philipp, C. Jacobs, E. Smit and A. Hering, "Systematic evaluation of foundation models for organ-level classification on CT scans", International Journal of Computer Assisted Radiology and Surgery, 2026.
Abstract DOI
A. Hunkemöller, T. Werncke, J. Dittrich, C. Schaefer-Prokop, F. Söbbeler, M. Avsar, J. Salman, A. Ruhparwar, R. Blasczyk, S. Besli, C. Figueiredo, A. Enzig-Strohm, F. Wacker and H. Shin, "Photon-counting CT for dynamic lung perfusion: validation of a low-dose protocol in a porcine lung transplantation model", European Radiology Experimental, 2026;10.
Abstract DOI
S. Gatidis, F. Peisen, A. Wagner, P. Choudja, A. Othman, A. Sanner, N. Grauhan, S. Kim, D. Graafen, L. Müller, T. Lo\ssau , J. Moltz, T. Kohlbrandt, A. Hering, C. La Fougère, K. Nikolaou and T. Küstner, "A longitudinal whole-body CT dataset with manually annotated tumor lesions", Scientific Data, 2026.
Abstract DOI
J. Spronck, L. van Eekelen, D. van Midden, J. Bogaerts, L. Tessier, V. Dechering, M. Demirel-Andishmand, G. de Souza, R. Nemeth, E. Munari, G. Bogina, I. Girolami, A. Eccher, B. Acs, C. Boyaci, N. Klubickova, M. Looijen-Salamon, S. Vos and F. Ciompi, "A tissue and cell-level annotated H&E and PD-L1 histopathology image dataset in non-small cell lung cancer", IEEE Journal of Biomedical and Health Informatics, 2026;():1-11.
DOI
B. Kincses, V. Pfaffenrot, K. Püchner, T. Spisak, K. Wiech, P. Koopmans and U. Bingel, "Layer-specific cortical processing dissociates sensory and cognitive influences on pain", Preprint, 2026.
Abstract DOI
E. Munari, R. Polati, P. Antonini, D. Segala, L. Cima, A. Porcaro, A. Antonelli, R. Bertolo, G. Bogina, F. Tavora, A. Acosta, A. Caliò, K. Faryna, G. Litjens, G. Martignoni and M. Brunelli, "Atypical intraductal proliferation (AIP) of the prostate: a borderline lesion with important clinical implications", Precision Pathology, 2026;1:100004.
DOI
R. Spaans, N. Khalili, G. Litjens and J. van Basten, "Tussen potentie en praktijk: AI als motor voor zorgtransformatie bij prostaatkanker", Tijdschrift voor Urologie, 2026.
Abstract DOI
Q. van Lohuizen, S. Fransen, H. Huisman, J. Wolterink, T. Kwee, D. Yakar and F. Simonis, "Aleatoric uncertainty in accelerated prostate MRI reconstruction: echo-train dropout versus Gaussian noise Monte Carlo sampling", Magnetic Resonance Materials in Physics, Biology and Medicine, 2026.
Abstract DOI
A. Schipper, P. Belgers, R. O'Connor, L. van de Wouw, L. Builtjes, J.S. Bosma, R. Kusters, S. Kurstjens, M. Rutten and B. van Ginneken, "Large Language Model Automated Extraction of Clinical Signs and Symptoms From Emergency Department Reports for Machine Learning Prediction Models: Development and Validation Study", JMIR Medical Informatics, 2026;14:e81500-e81500.
Abstract DOI
M. de Grauw, M. Westphal, E. Smit, E. Scholten, T. Lo\ssau , J. Moltz, S. Bottazzi, R. Cuocolo, A. D'Angelo, A. George, H. van Heusden, A. Liguori, V. Longo, L. Mannacio, N. Minh, A. Othman, A. Ponsiglione, J. Roosen, M. de Rooij, L. Russo, S. Schalekamp, M. Snoeren, A. Stanzione, S. Steinmetz, C. Verkroost, B. Vernhout, L. Xu, D. Yakar, M. Rutten, B. van Ginneken, M. Prokop and A. Hering, "Multicenter AI-versus Expert-Assisted RECIST Target Lesion Measurements in Follow-Up Body CT of Cancer Patients", Radiology Advances, 2026.
Abstract DOI
D. Pulido-Arias, M. Cleveland, J. Patel, Z. Wang, Y. Leng, T. Goncalves, M. Yao, A. Kim, D. Regge, K. Marias, M. Tsiknakis, H. Huisman, N. Papanikolaou, T. Consortium, J. Kalpathy-Cramer and C. Bridge, "Domain Generalization Mitigates Scanner-Induced Domain Shift in Medical Imaging", Journal of Imaging Informatics in Medicine, 2026.
Abstract DOI
A. Bouwmeester, T. Gootzen, M. Nobbenhuis, V. Rudaitis, C. van den Berg, H. van Beekhuizen, L. Alcalá, D. Smedts, N. Visser, V. Verhoef, T. Jonges, R. Zweemer, A. Leon-Catillo, C. Lems, J. de Hullu, J. van der Laak, M. Steenbeek and M. Simons, "Additional sectioning and AI -assisted diagnosis reveal underdiagnosis of serous (pre)malignancies in fallopian tube specimen from BRCA 1/2 carriers", Histopathology, 2026.
Abstract DOI
E. Baumann, L. Schäfer, F. Meeuwsen, R. Kirsch, I. Nagtegaal, M. Berger, H. Dawson and I. Zlobec, "MSAI-Path: Predicting Microsatellite Instability From Routine Histology Slides Without Reinventing the Wheel", Modern Pathology, 2026;39(1):100932.
Abstract DOI
J. Dixon-Douglas, D. Drubay, R. Salgado, B. Acs, J. van de Laark, Y. Yuan, M. Amgad, L. Cooper, Y. Hagos, K. AbdulJabbar, J. Meakin, B. Van Ginneken, H. Yan, J. Lemonnier, F. Penault-Llorca, M. Lacroix-Triki, H. Jounsuu, P. Kellokumpu-Lehtinen, S. Loibl, C. Denkert, G. Viale, M. Colleoni, C. Sotiriou, M. Piccart, M. Dieci, S. Demaria, R. Kammler, A. Wolff, S. Adams, S. Badve, R. Gray, G. Curigliano, A. Vincent-Salomon, T. Nielsen, L. Pusztai, F. Ciompi, S. Michiels and S. Loi, "Abstract PD11-02: Artificial Intelligence for Tumor-Infiltrating Lymphocytes in Early-Stage TNBC: Results of a Collaborative Prospective TIL Validation Challenge", Clinical Cancer Research, 2026;32:PD11-02-PD11-02.
Abstract DOI

Preprints

S. Moonemans, S. Ram, F. Meeuwsen, C. Lems, J. van der Laak, G. Litjens and F. Ciompi, "Democratising Pathology Co-Pilots: An Open Pipeline and Dataset for Whole-Slide Vision-Language Modelling", arXiv:2512.17326, 2026.
arXiv
C. Grisi, K. Faryna, N. Uysal, V. Agosti, E. Munari, S. Kammerer-Jacquet, P. Salles, Y. Tolkach, R. Büttner, S. Semko, M. Pikul, A. Heidenreich, J. van der Laak and G. Litjens, "Deep Learning From Routine Histology Improves Risk Stratification for Biochemical Recurrence in Prostate Cancer", arXiv:2603.14187, 2026.
Abstract DOI arXiv
C. Grisi, J. van der Laak and G. Litjens, "A Distributional Robustness Margin For Pathology Foundation Models", arXiv:2607.25497, 2026.
Abstract DOI arXiv
Q. Da, Y. Chen, M. Ju, Z. Ji, A. Zhou, W. Wang, M. Abikenari, P. Chikontwe, G. Larghero, B. Chen, P. Neidlinger, D. Zhong, S. Wang, W. Xu, D. Williamson, G. Corredor, S. Yang, L. Lu, X. Han, K. Yu, J. Huang, L. Barisoni, G. Litjens, A. Madabhushi, L. Zhu, C. Wang, J. Zhao and W. Hu, "Computational Pathology in the Era of Emerging Foundation and Agentic AI -- International Expert Perspectives on Clinical Integration and Translational Readiness", arXiv:2603.05884, 2026.
Abstract DOI arXiv
M. Stegeman, L. Philipp, F. van der Graaf, M. D'Amato, C. Grisi, L. Builtjes, J.S. Bosma, J. Lefkes, R. Weber, J. Meakin, T. Koopman, A. Mickan, M. Prokop, E. Smit, G. Litjens, J. van der Laak, B. van Ginneken, M. de Rooij, H. Huisman, C. Jacobs, F. Ciompi and A. Hering, "Designing UNICORN: a Unified Benchmark for Imaging in Computational Pathology, Radiology, and Natural Language", arXiv:2603.02790, 2026.
Abstract DOI arXiv
C. Lems, S. Moonemans, N. Klubíčková, B. Brattoli, T. Lee, S. Kim, V. Vilaplana, L. Pons, S. Hochman, M. Suárez-Franck, P. Fernandez, J. Drachneris, D. Petroska, R. Augulis, A. Laurinavicius, D. Oliveira, D. Montezuma, A. Bouwmeester, D. van Midden, A. Vos, S. Vos, J. van Ipenburg, M. Balkenhol, K. Winkler, I. Nagtegaal, K. Hebeda, U. Flucke, K. Grünberg, J. Skopal, B. Chohan, J. Temprana-Salvador, E. Munari, L. Cima, G. Querzoli, Y. Belisario, J. Faber, G. van Leenders, J. von der Thüsen, L. Brosens, R. de Krijger, P. Wesseling, S. Florquin, M. Maniewski, A. Kowalewski, R. Barna, D. Tiniakos, J. Gros, R. Donders, J. Maurits, M. Lu, C. Chen, F. Mahmood, J. van der Laak, N. Khalili, F. Meeuwsen and F. Ciompi, "DALPHIN: Benchmarking Digital Pathology AI Copilots Against Pathologists on an Open Multicentric Dataset", arXiv:2605.03544, 2026.
Abstract DOI arXiv

Papers in conference proceedings

L. Heil, R. van der Waerden, R. Volleberg, J. Thannhauser, J. van der Zande, T. Luttikholt, P. Cancian, X. Gu, B. van Ginneken, C. Gutierrez, I. Isgum, N. van Royen and S. Saitta, "Uncertainty Analysis in Intravascular Oct Segmentation", 2026 IEEE 23rd International Symposium on Biomedical Imaging (ISBI), 2026:1-5.
DOI
R. Weber, N. Rocholl, M. de Grauw, M. Prokop, E. Smit and A. Hering, "Data-driven Model Adaptation Enhances Lesion Segmentation", Bildverarbeitung für die Medizin 2026, 2026:482-489.
Abstract
J. Dusseljee, S. de Boer and A. Hering, "Kidney Cancer Detection Using 3D-based Latent Diffusion Models", Bildverarbeitung für die Medizin 2026, 2026:411-418.
Abstract
L. Builtjes and A. Hering, "Tracking Cancer Through Text: Longitudinal Extraction from Radiology Reports using Open-source Large Language Models", Bildverarbeitung für die Medizin 2026, 2026:381-386.
Abstract DOI
J. Tagscherer, S. de Boer, L. Philipp, F. van der Graaf, D. Peeters, J. Bosma, L. Leijten, B. Obreja, E. Smit and A. Hering, "Modular Pipeline for Rapidly Evaluating Foundation Models in Medical Imaging", Bildverarbeitung für die Medizin 2026, 2026:48-54.
Abstract
M. van Lente, K. Verdonschot, G. Laimer, S. van der Lei, M. Meijerink, R. Bale, H. Huisman, J. Fütterer and C. Overduin, "Deep learning-based ablation margin assessment in thermal ablation of colorectal liver metastasis: preliminary results of an automatic segmentation workflow", Medical Imaging 2026: Image-Guided Procedures, Robotic Interventions, and Modeling, 2026:38.
DOI
A. Arab, V. Garcia, S. Kahaki, M. van Rijthoven, R. Salgado, B. Gallas, F. Ciompi, N. Petrick and W. Chen, "Assessment of AI segmentation models in histopathology whole slide images: the effect of the unit of analysis", Medical Imaging 2026: Digital and Computational Pathology, 2026:31.
DOI

Abstracts

D. Peeters, B. Obreja, N. Antonissen, Z. Saghir, U. Pastorino, G. De Bock, R. Vliegenthart, M. Prokop and C. Jacobs, "Benchmarking of Artificial Intelligence and Radiologists for Indeterminate Lung Nodule Malignancy Risk Estimation on Screening CT: Results of the LUNA25 Challenge", European Congress of Radiology, 2026.
Abstract
A. Cerrato Nieto, E. Scholten, S. Schalekamp, M. Prokop and C. Jacobs, "Benchmarking lung tumour segmentation models: stratified performance of deep learning models across tumour sizes and cancer stages", European Congress of Radiology, 2026.
Abstract
M. Vitale, M. Vegter, C. Jacobs and M. Boenink, "Principles for AI-enabled population screening", European Congress of Radiology, 2026.
Abstract
N. Antonissen, S. Schalekamp, H. Hahn, K. van Leeuwen and C. Jacobs, "Commercially available AI products for CT-based lung cancer screening: capabilities, clinical evidence, and alignment with international screening frameworks", European Congress of Radiology, 2026.
Abstract
R. Dinnessen, N. Antonissen, D. Peeters, H. Gietema, F. Mohamed Hoesein, E. Scholten, C. Schaefer-Prokop and C. Jacobs, "Performance and generalisability of a screening-trained deep learning model for pulmonary nodule malignancy risk estimation on a multicentre dataset of incidental nodules", European Congress of Radiology, 2026.
Abstract
L. Leijten, E. van der Heijden, E. Aarntzen, R. Verhoeven and C. Jacobs, "Deep-learning based malignancy risk estimation of pulmonary nodules in PET/CT imaging", European Congress of Radiology, 2026.
Abstract
M. Vitale, M. Vegter, C. Jacobs and M. Boenink, "Algorithmic Fairness unfolded: collaborative ethnography within a medical imaging AI lab for Lung Cancer Screening", European Congress of Radiology, 2026.
Abstract

PhD theses

J. Twilt, "Artificial Intelligence and Biparametric MRI in Prostate Cancer Detection", PhD thesis, 2026.
Abstract Url
P. Venditelli, "Learning from histopathology images: AI-driven biomarkers for pancreatic ductal adenocarcinoma", PhD thesis, 2026.
Abstract Url
A. Saha, "Artificial Intelligence x Prostate Cancer Detection on MRI", PhD thesis, 2026.
Abstract Url

Other publications

B. Abrahamsen, J.S. Bosma, H. Huisman and M. Elschot, "A Federated Benchmark for Clinical Natural Language Processing (FedDRAGON)", Studies in Health Technology and Informatics, 2026.
Abstract DOI