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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
M. Rijthoven, W. Aswolinskiy, L. Tessier, R. Salgado, J. van der Laak, F. Ciompi, T. consortium, M. van Rijthoven, J. van der Laak, 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. Dixon-Douglas, S. Michiels, R. Donders, S. Maurits, M. Groeneveld, A. Mickan, J. Meakin, B. van Ginneken, 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. Arab, W. Chen, V. Garcia, N. Petrick, B. Gallas, 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 and K. Kim, "Analysis of computational tumor-infiltrating lymphocytes in breast cancer from the results of the TIGER challenge",
Nature Communications,
2026.
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.
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.
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.
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.
J. Tagscherer, S. de Boer, L. Philipp, F. van der Graaf, D. Peeters, J. Bosma, L. Leijten, B. Obreja, E. Smit and A. Hering, "EvalBlocks: A Modular Pipeline for Rapidly Evaluating Foundation Models in Medical Imaging",
2026.
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.
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.
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.
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.
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.
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.