Publications
2023
Papers in international journals
- H. ten Berg, B. van Bakel, L. van de Wouw, K. Jie, A. Schipper, H. Jansen, R. O’Connor, B. van Ginneken and S. Kurstjens, "ChatGPT and Generating a Differential Diagnosis Early in an Emergency Department Presentation", Annals of Emergency Medicine, 2023.
- S. Vinayahalingam, S. Kempers, J. Schoep, T. Hsu, D. Moin, B. van Ginneken, T. Flügge, M. Hanisch and T. Xi, "Intra-oral scan segmentation using deep learning", BMC Oral Health, 2023;23.
- C. Jacobs, "Challenges and outlook in the management of pulmonary nodules detected on CT", European Radiology, 2023.
- K. Venkadesh, T. Aleef, E. Scholten, Z. Saghir, M. Silva, N. Sverzellati, U. Pastorino, B. van Ginneken, M. Prokop and C. Jacobs, "Prior CT Improves Deep Learning for Malignancy Risk Estimation of Screening-detected Pulmonary Nodules", Radiology, 2023;308(2):e223308.
- W. Hendrix, M. Rutten, N. Hendrix, B. van Ginneken, C. Schaefer-Prokop, E. Scholten, M. Prokop and C. Jacobs, "Trends in the incidence of pulmonary nodules in chest computed tomography: 10-year results from two Dutch hospitals", European Radiology, 2023.
- J. Bokhorst, I. Nagtegaal, F. Fraggetta, S. Vatrano, W. Mesker, M. Vieth, J. van der Laak and F. Ciompi, "Deep learning for multi-class semantic segmentation enables colorectal cancer detection and classification in digital pathology images", Nature Scientific Reports, 2023;13:8398.
- B. Laarhuis, M. Janssen, M. Simons, L. van Kalmthout, M. van der Doelen, S. Peters, H. Westdorp, I. van Oort, G. Litjens, M. Gotthardt, J. Nagarajah, N. Mehra and B. Privé, "Tumoral Ki67 and PSMA Expression in Fresh Pre-PSMA-RLT Biopsies and Its Relation With PSMA-PET Imaging and Outcomes of PSMA-RLT in Patients With mCRPC.", Clinical Genitourinary Cancer, 2023.
- M. Schuurmans, N. Alves, P. Vendittelli, H. Huisman and J. Hermans, "Artificial Intelligence in Pancreatic Ductal Adenocarcinoma Imaging: A Commentary on Potential Future Applications.", Gastroenterology, 2023.
- J. Bokhorst, I. Nagtegaal, I. Zlobec, H. Dawson, K. Sheahan, F. Simmer, R. Kirsch, M. Vieth, A. Lugli, J. van der Laak and F. Ciompi, "Semi-Supervised Learning to Automate Tumor Bud Detection in Cytokeratin-Stained Whole-Slide Images of Colorectal Cancer", Cancers, 2023;15(7):2079.
- G. Sidorenkov, R. Stadhouders, C. Jacobs, F. Mohamed Hoesein, H. Gietema, K. Nackaerts, Z. Saghir, M. Heuvelmans, H. Donker, J. Aerts, R. Vermeulen, A. Uitterlinden, V. Lenters, J. van Rooij, C. Schaefer-Prokop, H. Groen, P. de Jong, R. Cornelissen, M. Prokop, G. de Bock and R. Vliegenthart, "Multi-source data approach for personalized outcome prediction in lung cancer screening: update from the NELSON trial.", European journal of epidemiology, 2023;38(4):445-454.
- W. Xie, C. Jacobs, J. Charbonnier and B. van Ginneken, "Dense regression activation maps for lesion segmentation in CT scans of COVID-19 patients", Medical Image Analysis, 2023;86:102771.
- L. van Eekelen, G. Litjens and K. Hebeda, "Artificial intelligence in bone marrow histological diagnostics: potential applications and challenges.", Pathobiology, 2023.
- S. Sadr, H. Mohammad-Rahimi, S. Motamedian, S. Zahedrozegar, P. Motie, S. Vinayahalingam, O. Dianat and A. Nosrat, "Deep Learning for Detection of Periapical Radiolucent Lesions: A Systematic Review and Meta-analysis of Diagnostic Test Accuracy.", Journal of endodontics, 2023;49(3):248-261.e3.
- J. Linmans, S. Elfwing, J. van der Laak and G. Litjens, "Predictive uncertainty estimation for out-of-distribution detection in digital pathology.", Medical Image Analysis, 2023;83:102655.
- K. Leeuwen, M. Becks, D. Grob, F. de Lange, J. Rutten, S. Schalekamp, M. Rutten, B. van Ginneken, M. de Rooij and F. Meijer, "AI-support for the detection of intracranial large vessel occlusions: One-year prospective evaluation", Heliyon, 2023;9(8).
- N. Hendrix, W. Hendrix, K. van Dijke, B. Maresch, M. Maas, S. Bollen, A. Scholtens, M. de Jonge, L. Ong, B. van Ginneken and M. Rutten, "Musculoskeletal radiologist-level performance by using deep learning for detection of scaphoid fractures on conventional multi-view radiographs of hand and wrist", European Radiology, 2023;33:1575-1588.
- K. van Leeuwen, M. de Rooij, S. Schalekamp, B. van Ginneken and M. Rutten, "Clinical use of artificial intelligence products for radiology in the Netherlands between 2020 and 2022", European Radiology, 2023.
- J. Thagaard, G. Broeckx, D. Page, C. Jahangir, S. Verbandt, Z. Kos, R. Gupta, R. Khiroya, K. Abduljabbar, G. Acosta Haab, B. Acs, G. Akturk, J. Almeida, I. Alvarado‐Cabrero, M. Amgad, F. Azmoudeh‐Ardalan, S. Badve, N. Baharun, E. Balslev, E. Bellolio, V. Bheemaraju, K. Blenman, L. Mendonça Botinelly Fujimoto, N. Bouchmaa, O. Burgues, A. Chardas, M. U Chon Cheang, F. Ciompi, L. Cooper, A. Coosemans, G. Corredor, A. Dahl, F. Dantas Portela, F. Deman, S. Demaria, J. Doré Hansen, S. Dudgeon, T. Ebstrup, M. Elghazawy, C. Fernandez‐Martín, S. Fox, W. Gallagher, J. Giltnane, S. Gnjatic, P. Gonzalez‐Ericsson, A. Grigoriadis, N. Halama, M. Hanna, A. Harbhajanka, S. Hart, J. Hartman, S. Hauberg, S. Hewitt, A. Hida, H. Horlings, Z. Husain, E. Hytopoulos, S. Irshad, E. Janssen, M. Kahila, T. Kataoka, K. Kawaguchi, D. Kharidehal, A. Khramtsov, U. Kiraz, P. Kirtani, L. Kodach, K. Korski, A. Kovács, A. Laenkholm, C. Lang‐Schwarz, D. Larsimont, J. Lennerz, M. Lerousseau, X. Li, A. Ly, A. Madabhushi, S. Maley, V. Manur Narasimhamurthy, D. Marks, E. McDonald, R. Mehrotra, S. Michiels, 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, A. Rahman, N. Rajpoot, B. Rapoport, T. Rau, J. Reis‐Filho, J. Ribeiro, D. Rimm, A. Roslind, A. Vincent‐Salomon, M. Salto‐Tellez, J. Saltz, S. Sayed, E. Scott, K. Siziopikou, C. Sotiriou, A. Stenzinger, M. Sughayer, D. Sur, S. Fineberg, F. Symmans, S. Tanaka, T. Taxter, S. Tejpar, J. Teuwen, E. Thompson, T. Tramm, W. Tran, J. van der Laak, P. van Diest, G. Verghese, G. Viale, M. Vieth, N. Wahab, T. Walter, Y. Waumans, H. Wen, W. Yang, Y. Yuan, R. Zin, S. Adams, J. Bartlett, S. Loibl, C. Denkert, P. Savas, S. Loi, R. Salgado and E. Specht Stovgaard, "Pitfalls in machine learning‐based assessment of tumor‐infiltrating lymphocytes in breast cancer: A report of the International Immuno‐Oncology Biomarker Working Group on Breast Cancer", The Journal of Pathology, 2023;260:498-513.
- B. Katende, M. Bresser, M. Kamele, L. Chere, M. Tlahali, R. Erhardt, J. Muhairwe, I. Ayakaka, T. Glass, M. Ruhwald, B. van Ginneken, K. Murphy, M. de Vos, A. Amstutz, M. Mareka, S. Mooko, K. Reither and L. González Fernández, "Impact of a multi-disease integrated screening and diagnostic model for COVID-19, TB, and HIV in Lesotho", PLOS Global Public Health, 2023;3:e0001488.
- J. Bosma, A. Saha, M. Hosseinzadeh, I. Slootweg, M. de Rooij and H. Huisman, "Semi-supervised Learning with Report-guided Pseudo Labels for Deep Learning-based Prostate Cancer Detection Using Biparametric MRI", Radiology: Artificial Intelligence, 2023:e230031.
- M. Smit, F. Ciompi, J. Bokhorst, G. van Pelt, O. Geessink, H. Putter, R. Tollenaar, J. van Krieken, W. Mesker and J. van der Laak, "Deep learning based tumor–stroma ratio scoring in colon cancer correlates with microscopic assessment", Journal of Pathology Informatics, 2023.
- J. van der Graaf, R. Kroeze, C. Buckens, N. Lessmann and M. van Hooff, "MRI image features with an evident relation to low back pain: a narrative review", European Spine Journal, 2023:1-12.
- J. Bokhorst, F. Ciompi, S. Öztürk, A. Oguz Erdogan, M. Vieth, H. Dawson, R. Kirsch, F. Simmer, K. Sheahan, A. Lugli, I. Zlobec, J. van der Laak and I. Nagtegaal, "Fully Automated Tumor Bud Assessment in Hematoxylin and Eosin-Stained Whole Slide Images of Colorectal Cancer", Modern Pathology, 2023;36:100233.
- C. De Vente, K. Vermeer, N. Jaccard, H. Wang, H. Sun, F. Khader, D. Truhn, T. Aimyshev, Y. Zhanibekuly, T. Le, A. Galdran, M. Ballester, G. Carneiro, R. Devika, P. Hrishikesh, D. Puthussery, H. Liu, Z. Yang, S. Kondo, S. Kasai, E. Wang, A. Durvasula, J. Heras, M. Zapata, T. Araújo, G. Aresta, H. Bogunović, M. Arikan, Y. Lee, H. Cho, Y. Choi, A. Qayyum, I. Razzak, B. Van Ginneken, H. Lemij and C. Sánchez, "AIROGS: Artificial Intelligence for RObust Glaucoma Screening Challenge", IEEE Transactions on Medical Imaging, 2023:1-1.
- N. Alves, J. Bosma, K. Venkadesh, C. Jacobs, Z. Saghir, M. de Rooij, J. Hermans and H. Huisman, "Prediction Variability to Identify Reduced AI Performance in Cancer Diagnosis at MRI and CT", Radiology, 2023;308.
- D. Page, G. Broeckx, C. Jahangir, S. Verbandt, R. Gupta, J. Thagaard, R. Khiroya, Z. Kos, K. Abduljabbar, G. Acosta Haab, B. Acs, G. Akturk, J. Almeida, I. Alvarado‐Cabrero, F. Azmoudeh‐Ardalan, S. Badve, N. Baharun, E. Bellolio, V. Bheemaraju, K. Blenman, L. Mendonça Botinelly Fujimoto, N. Bouchmaa, O. Burgues, M. Cheang, F. Ciompi, L. Cooper, A. Coosemans, G. Corredor, F. Dantas Portela, F. Deman, S. Demaria, S. Dudgeon, M. Elghazawy, S. Ely, C. Fernandez‐Martín, S. Fineberg, S. Fox, W. Gallagher, J. Giltnane, S. Gnjatic, P. Gonzalez‐Ericsson, A. Grigoriadis, N. Halama, M. Hanna, A. Harbhajanka, A. Hardas, S. Hart, J. Hartman, S. Hewitt, A. Hida, H. Horlings, Z. Husain, E. Hytopoulos, S. Irshad, E. Janssen, M. Kahila, T. Kataoka, K. Kawaguchi, D. Kharidehal, A. Khramtsov, U. Kiraz, P. Kirtani, L. Kodach, K. Korski, A. Kovács, A. Laenkholm, C. Lang‐Schwarz, D. Larsimont, J. Lennerz, M. Lerousseau, X. Li, A. Ly, A. Madabhushi, S. Maley, V. Manur Narasimhamurthy, D. Marks, E. McDonald, R. Mehrotra, S. Michiels, 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, A. Rahman, N. Rajpoot, B. Rapoport, T. Rau, J. Reis‐Filho, J. Ribeiro, D. Rimm, A. Vincent‐Salomon, M. Salto‐Tellez, J. Saltz, S. Sayed, 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, P. van Diest, G. Verghese, G. Viale, M. Vieth, N. Wahab, T. Walter, Y. Waumans, H. Wen, W. Yang, Y. Yuan, S. Adams, J. Bartlett, S. Loibl, C. Denkert, P. Savas, S. Loi, R. Salgado and E. Specht Stovgaard, "Spatial analyses of immune cell infiltration in cancer: current methods and future directions: A report of the International Immuno‐Oncology Biomarker Working Group on Breast Cancer", The Journal of Pathology, 2023;260:514-532.
- L. Thijssen, M. de Rooij, J. Barentsz and H. Huisman, "Radiomics based automated quality assessment for T2W prostate MR images", European Journal of Radiology, 2023.
- B. de Wilde, F. Joosten, W. Venderink, M. Davidse, J. Geurts, H. Kruijt, A. Vermeulen, B. Martens, M. Schyns, J. Huige, M. de Boer, B. Tonino, H. Zandvoort, K. Lammert, H. Parviainen, A. Vuorinen, S. Syväranta, R. Vogels, W. Prins, A. Coppola, N. Bossa, R. ten Broek and H. Huisman, "Inter-and Intra-Observer Variability and the Effect of Experience in Cine-MRI for Adhesion Detection", Journal of Imaging, 2023;9(3):55.
- M. Palmer, J. Seddon, M. van der Zalm, A. Hesseling, P. Goussard, H. Schaaf, J. Morrison, B. van Ginneken, J. Melendez, E. Walters and K. Murphy, "Optimising computer aided detection to identify intra-thoracic tuberculosis on chest x-ray in South African children", PLOS Global Public Health, 2023;3:e0001799.
- L. Menotti, G. Silvello, M. Atzori, S. Boytcheva, F. Ciompi, G. Di Nunzio, F. Fraggetta, F. Giachelle, O. Irrera, S. Marchesin, N. Marini, H. Müller and T. Primov, "Modelling digital health data: The ExaMode ontology for computational pathology", Journal of Pathology Informatics, 2023;14:100332.
- W. Xie, C. Jacobs, J. Charbonnier, D. Slebos and B. van Ginneken, "Emphysema subtyping on thoracic computed tomography scans using deep neural networks", Scientific Reports, 2023;13:14147.
- B. van den Beukel, B. de Wilde, F. Joosten, H. van Goor, W. Venderink, H. Huisman and R. ten Broek, "Quantifiable Measures of Abdominal Wall Motion for Quality Assessment of Cine-MRI Slices in Detection of Abdominal Adhesions", Journal of Imaging, 2023;9(5).
- P. Bándi, M. Balkenhol, M. van Dijk, M. Kok, B. van Ginneken, J. van der Laak and G. Litjens, "Continual learning strategies for cancer-independent detection of lymph node metastases", Medical Image Analysis, 2023;85:102755.
Preprints
- 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", arXiv:2306.12217, 2023.
- 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, M. Blaschko, F. Büttner, M. Cardoso, V. Cheplygina, J. Chen, E. Christodoulou, B. Cimini, G. Collins, K. Farahani, L. Ferrer, A. Galdran, B. van Ginneken, B. Glocker, P. Godau, R. Haase, D. Hashimoto, M. Hoffman, M. Huisman, F. Isensee, P. Jannin, C. Kahn, D. Kainmueller, B. Kainz, A. Karargyris, A. Karthikesalingam, H. Kenngott, 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, P. Mattson, 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, M. van Smeden, R. Summers, A. Taha, A. Tiulpin, S. Tsaftaris, B. Van Calster, G. Varoquaux, M. Wiesenfarth, Z. Yaniv, P. Jäger and L. Maier-Hein, "Understanding metric-related pitfalls in image analysis validation", arXiv:2302.01790, 2023.
- B. de Wilde, A. Saha, R. ten Broek and H. Huisman, "Medical diffusion on a budget: textual inversion for medical image generation", arXiv:2303.13430, 2023.
Papers in conference proceedings
- A. Saha, J. Bosma, J. Twilt, B. van Ginneken, D. Yakar, M. Elschot, J. Veltman, J. Fütterer, M. de Rooij and H. Huisman, "Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI: The PI-CAI Challenge", Medical Imaging with Deep Learning, 2023.
- J. Spronck, T. Gelton, L. van Eekelen, J. Bogaerts, L. Tessier, M. van Rijthoven, L. van der Woude, M. van den Heuvel, W. Theelen, J. van der Laak and F. Ciompi, "nnUNet meets pathology: bridging the gap for application to whole-slide images and computational biomarkers", Medical Imaging with Deep Learning, 2023.
- J. Bosma, D. Peeters, N. Alves, A. Saha, Z. Saghir, C. Jacobs and H. Huisman, "Reproducibility of Training Deep Learning Models for Medical Image Analysis", Medical Imaging with Deep Learning, 2023.
- D. Schouten and G. Litjens, "PythoStitcher: an iterative approach for stitching digitized tissue fragments into full resolution whole-mount reconstructions", Medical Imaging, 2023;12471:1247118.
- P. Vendittelli, J. Bokhorst, E. Smeets, V. Kryklyva, L. Brosens, C. Verbeke and G. Litjens, "Automatic quantification of TSR as a prognostic marker for pancreatic cancer.", Medical Imaging with Deep Learning, 2023.
Abstracts
- Q. van Lohuizen, C. Roest, F. Simonis, S. Fransen, T. Kwee, D. Yakar and H. Huisman, "Diagnostic AI to speed up MRI protocols by identifying redundant sequences: are all diffusion-weighted prostate MRI sequences necessary?", Annual Meeting of the Radiological Society of North America, 2023.
- J. Twilt, A. Saha, J. Bosma, B. van Ginneken, D. Yakar, M. Elschot, J. Veltman, J. Fütterer, H. Huisman and M. de Rooij, "Diagnostic Value of Dynamic Contrast-Enhanced MRI for the Detection of Clinically Significant Prostate Cancer in a Multi-Reader Study: Preliminary Results from the PI-CAI Consortium", European Congress of Radiology, 2023.
- R. Lomans, J. van der Laak, I. Nagtegaal, F. Ciompi and R. van der Post, "Deep learning for multi-class cell detection in H&E-stained slides of diffuse gastric cancer", European Congress of Pathology, 2023.
- K. van Leeuwen, D. Hedderich and S. Schalekamp, "Potential risk of off-label use of commercially available AI-based software for radiology", European Congress of Radiology, 2023.
- R. Leon-Ferre, J. Carter, D. Zahrieh, J. Sinnwell, R. Salgado, V. Suman, D. Hillman, J. Boughey, K. Kalari, F. Couch, J. Ingle, M. Balkenkohl, F. Ciompi, J. van der Laak and M. Goetz, "Abstract P2-11-34: Mitotic spindle hotspot counting using deep learning networks is highly associated with clinical outcomes in patients with early-stage triple-negative breast cancer who did not receive systemic therapy", Cancer Research, 2023;83:P2-11-34-P2-11-34.
- R. Lomans, R. van der Post and F. Ciompi, "Interactive Cell Detection in H&E-stained slides of Diffuse Gastric Cancer", Medical Imaging with Deep Learning, 2023.
- M. D'Amato, M. Balkenhol, M. van Rijthoven, J. van der Laak and F. Ciompi, "On the robustness of regressing tumor percentage as an explainable detector in histopathology whole-slide images", Medical Imaging with Deep Learning, 2023.
- D. Peeters, N. Alves, K. Venkadesh, R. Dinnessen, Z. Saghir, E. Scholten, H. Huisman, C. Schaefer-Prokop, R. Vliegenthart, M. Prokop and C. Jacobs, "The effect of applying an uncertainty estimation method on the performance of a deep learning model for nodule malignancy risk estimation", European Congress of Radiology, 2023.
- N. Antonissen, K. Venkadesh, H. Gietema, R. Vliegenthart, Z. Saghir, E. Scholten, M. Prokop, C. Schaefer-Prokop and C. Jacobs, "Retrospective validation of nodule management based on deep learning-based malignancy thresholds in lung cancer screening", European Congress of Radiology, 2023.
- A. Saha, J. Bosma, J. Twilt, B. van Ginneken, D. Yakar, M. Elschot, J. Veltman, J. Fütterer, M. de Rooij and H. Huisman, "Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI: The PI-CAI Challenge", European Congress of Radiology, 2023.
- J. Twilt, A. Saha, J. Bosma, B. van Ginneken, D. Yakar, M. Elschot, J. Veltman, J. Fütterer, H. Huisman and M. de Rooij, "EAU Plenary Gamechanging Session - Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI: Preliminary Results from the PI-CAI Challenge", Annual European Association of Urology Congress, 2023.
- B. Guevara, N. Marini, S. Marchesin, W. Aswolinskiy, R. Schlimbach, D. Podareanu and F. Ciompi, "Caption generation from histopathology whole-slide images using pre-trained transformers", Medical Imaging with Deep Learning, 2023.
PhD theses
- E. Çallı, "Deep learning methods towards clinically applicable Chest X-ray interpretation systems", PhD thesis, 2023.
- A. Patel, "Automated Image Analysis of Cranial Non-Contrast CT", PhD thesis, 2023.
- W. Xie, "Deep Learning for Treatment Planning in Chronic Obstructive Pulmonary Diseases", PhD thesis, 2023.
Master theses
- S. Vyawahare, K. Venkadesh and C. Jacobs, "Automated segmentation of subsolid pulmonary nodules in CT scans using deep learning", Master thesis, 2023.
- L. Philipp, "Body Composition Assessment in 3D CT Images", Master thesis, 2023.
- R. Geurtjens, D. Peeters and C. Jacobs, "Self-supervised Out-of-Distribution detection for medical imaging", Master thesis, 2023.
Other publications
- M. Aubreville, N. Stathonikos, C. Bertram, R. Klopfleisch, N. Hoeve, F. Ciompi, F. Wilm, C. Marzahl, T. Donovan, A. Maier, M. Veta and K. Breininger, "Abstract: the MIDOG Challenge 2021", Bildverarbeitung fur die Medizin, Workshop, 2023:115-115.