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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",
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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",
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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"",
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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",
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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?",
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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,
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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,
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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,
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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",
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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",
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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",
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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",
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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",
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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,
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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",
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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",
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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,
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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",
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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",
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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",
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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,
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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,
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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,
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T. Perik, N. Alves, J. Hermans and H. Huisman, "Automated Quantitative Analysis of CT Perfusion to Classify Vascular Phenotypes of Pancreatic Ductal Adenocarcinoma",
Cancer,
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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,
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E. Chelebian, C. Avenel, F. Ciompi and C. Wählby, "DEPICTER: Deep representation clustering for histology annotation",
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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,
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K. Faryna, J. van der Laak and G. Litjens, "Automatic data augmentation to improve generalization of deep learning in H&E stained histopathology",
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D. Schouten, J. van der Laak, B. van Ginneken and G. Litjens, "Full resolution reconstruction of whole-mount sections from digitized individual tissue fragments",
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The Journal of Pathology,
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J. Linmans, G. Raya, J. van der Laak and G. Litjens, "Diffusion models for out-of-distribution detection in digital pathology",
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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",
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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",
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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,
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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,
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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",
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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,
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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,
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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,
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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",
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Medical Image Analysis,
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W. Xie, C. Jacobs, J. Charbonnier and B. van Ginneken, "Structure and position-aware graph neural network for airway labeling",
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Clinical Infectious Diseases,
2024.
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",
arXiv:2401.02192,
2024.
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.
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.
C. Grisi, G. Litjens and J. van der Laak, "Masked Attention as a Mechanism for Improving Interpretability of Vision Transformers",
arXiv:2404.18152,
2024.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
N. Hendrix, "Artificial Intelligence for Computer Aided Diagnosis of Scaphoid Fractures and Associated Instability on Conventional Radiography",
PhD thesis,
2024.
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.
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.