Publications

2023

Papers in international journals

1. 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.
   Abstract DOI PMID
2. 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.
   Abstract DOI PMID
3. C. Jacobs, "Challenges and outlook in the management of pulmonary nodules detected on CT", European Radiology, 2023.
   Abstract DOI PMID
4. 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.
   Abstract DOI PMID Algorithm
5. 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.
   Abstract DOI PMID
6. 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.
   Abstract DOI PMID
7. 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.
   Abstract DOI PMID
8. 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.
   Abstract DOI PMID
9. 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.
   Abstract DOI PMID
10. 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.
    Abstract DOI PMID
11. 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.
    Abstract DOI PMID Code
12. L. van Eekelen, G. Litjens and K. Hebeda, "Artificial intelligence in bone marrow histological diagnostics: potential applications and challenges.", Pathobiology, 2023.
    Abstract DOI PMID
13. 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.
    Abstract DOI PMID
14. 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.
    Abstract DOI PMID
15. 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).
    Abstract DOI
16. 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.
    Abstract DOI
17. 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.
    Abstract DOI
18. 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.
    Abstract DOI
19. 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.
    Abstract DOI
20. 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.
    Abstract DOI
21. 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.
    Abstract DOI
22. 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.
    Abstract DOI
23. 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.
    Abstract DOI
24. 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.
    Abstract DOI
25. 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.
    Abstract DOI
26. 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.
    Abstract DOI
27. 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.
    Abstract DOI
28. 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.
    Abstract DOI
29. 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.
    Abstract DOI
30. 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.
    Abstract DOI
31. 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.
    Abstract DOI
32. 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).
    Abstract DOI
33. 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.
    Abstract DOI

Preprints

1. 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.
   Abstract arXiv
2. 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.
   Abstract arXiv
3. 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.
   Abstract arXiv

Papers in conference proceedings

1. 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.
   Abstract Url
2. 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.
   Abstract Url
3. 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.
   Abstract Url
4. 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.
   Abstract DOI
5. 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.
   Abstract Url

Abstracts

1. 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.
   Abstract
2. 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.
   Abstract
3. 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.
   Abstract
4. 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.
   Abstract
5. 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.
   Abstract DOI
6. 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.
   Abstract
7. 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.
   Abstract
8. 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.
   Abstract
9. 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.
   Abstract
10. 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.
    Abstract
11. 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.
    Abstract
12. 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.
    Abstract

PhD theses

1. E. Çallı, "Deep learning methods towards clinically applicable Chest X-ray interpretation systems", PhD thesis, 2023.
   Abstract Url
2. A. Patel, "Automated Image Analysis of Cranial Non-Contrast CT", PhD thesis, 2023.
   Abstract Url
3. W. Xie, "Deep Learning for Treatment Planning in Chronic Obstructive Pulmonary Diseases", PhD thesis, 2023.
   Abstract Url

Master theses

1. S. Vyawahare, K. Venkadesh and C. Jacobs, "Automated segmentation of subsolid pulmonary nodules in CT scans using deep learning", Master thesis, 2023.
   Abstract
2. L. Philipp, "Body Composition Assessment in 3D CT Images", Master thesis, 2023.
   Abstract
3. R. Geurtjens, D. Peeters and C. Jacobs, "Self-supervised Out-of-Distribution detection for medical imaging", Master thesis, 2023.
   Abstract

Other publications

1. 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.
   Abstract DOI