Publications
2022
Papers in international journals
- P. Bilic, P. Christ, H. Li, E. Vorontsov, A. Ben-Cohen, G. Kaissis, A. Szeskin, C. Jacobs, G. Mamani, G. Chartrand, F. Lohöfer, J. Holch, W. Sommer, F. Hofmann, A. Hostettler, N. Lev-Cohain, M. Drozdzal, M. Amitai, R. Vivanti, J. Sosna, I. Ezhov, A. Sekuboyina, F. Navarro, F. Kofler, J. Paetzold, S. Shit, X. Hu, J. Lipková, M. Rempfler, M. Piraud, J. Kirschke, B. Wiestler, Z. Zhang, C. Hülsemeyer, M. Beetz, F. Ettlinger, M. Antonelli, W. Bae, M. Bellver, L. Bi, H. Chen, G. Chlebus, E. Dam, Q. Dou, C. Fu, B. Georgescu, X. Giró-i-Nieto, F. Gruen, X. Han, P. Heng, J. Hesser, J. Moltz, C. Igel, F. Isensee, P. Jäger, F. Jia, K. Kaluva, M. Khened, I. Kim, J. Kim, S. Kim, S. Kohl, T. Konopczynski, A. Kori, G. Krishnamurthi, F. Li, H. Li, J. Li, X. Li, J. Lowengrub, J. Ma, K. Maier-Hein, K. Maninis, H. Meine, D. Merhof, A. Pai, M. Perslev, J. Petersen, J. Pont-Tuset, J. Qi, X. Qi, O. Rippel, K. Roth, I. Sarasua, A. Schenk, Z. Shen, J. Torres, C. Wachinger, C. Wang, L. Weninger, J. Wu, D. Xu, X. Yang, S. Yu, Y. Yuan, M. Yue, L. Zhang, J. Cardoso, S. Bakas, R. Braren, V. Heinemann, C. Pal, A. Tang, S. Kadoury, L. Soler, B. van Ginneken, H. Greenspan, L. Joskowicz and B. Menze, "The Liver Tumor Segmentation Benchmark (LiTS)", Medical Image Analysis, 2022;84:102680.
- M. Aubreville, N. Stathonikos, C. Bertram, R. Klopfleisch, N. Ter Hoeve, F. Ciompi, F. Wilm, C. Marzahl, T. Donovan, A. Maier, J. Breen, N. Ravikumar, Y. Chung, J. Park, R. Nateghi, F. Pourakpour, R. Fick, S. Ben Hadj, M. Jahanifar, A. Shephard, J. Dexl, T. Wittenberg, S. Kondo, M. Lafarge, V. Koelzer, J. Liang, Y. Wang, X. Long, J. Liu, S. Razavi, A. Khademi, S. Yang, X. Wang, R. Erber, A. Klang, K. Lipnik, P. Bolfa, M. Dark, G. Wasinger, M. Veta and K. Breininger, "Mitosis domain generalization in histopathology images - The MIDOG challenge.", Medical Image Analysis, 2022;84:102699.
- L. Adams, M. Makowski, G. Engel, M. Rattunde, F. Busch, P. Asbach, S. Niehues, S. Vinayahalingam, B. van Ginneken, G. Litjens and K. Bressem, "Dataset of prostate MRI annotated for anatomical zones and cancer.", Data in brief, 2022;45:108739.
- S. Vinayahalingam, N. van Nistelrooij, B. van Ginneken, K. Bressem, D. Tröltzsch, M. Heiland, T. Flügge and R. Gaudin, "Detection of mandibular fractures on panoramic radiographs using deep learning.", Scientific reports, 2022;12(1):19596.
- E. Calli, B. Van Ginneken, E. Sogancioglu and K. Murphy, "FRODO: An in-depth analysis of a system to reject outlier samples from a trained neural network.", IEEE transactions on medical imaging, 2022;PP.
- S. Jarkman, M. Karlberg, M. Pocevičiūtė, A. Bodén, P. Bándi, G. Litjens, C. Lundström, D. Treanor and J. van der Laak, "Generalization of Deep Learning in Digital Pathology: Experience in Breast Cancer Metastasis Detection.", Cancers, 2022;14(21).
- C. Mercan, M. Balkenhol, R. Salgado, M. Sherman, P. Vielh, W. Vreuls, A. Polónia, H. Horlings, W. Weichert, J. Carter, P. Bult, M. Christgen, C. Denkert, K. van de Vijver, J. Bokhorst, J. van der Laak and F. Ciompi, "Deep learning for fully-automated nuclear pleomorphism scoring in breast cancer.", NPJ breast cancer, 2022;8(1):120.
- S. Marchesin, F. Giachelle, N. Marini, M. Atzori, S. Boytcheva, G. Buttafuoco, F. Ciompi, G. Di Nunzio, F. Fraggetta, O. Irrera, H. Müller, T. Primov, S. Vatrano and G. Silvello, "Empowering digital pathology applications through explainable knowledge extraction tools.", Journal of pathology informatics, 2022;13:100139.
- T. Eschert, F. Schwendicke, J. Krois, L. Bohner, S. Vinayahalingam and M. Hanisch, "A Survey on the Use of Artificial Intelligence by Clinicians in Dentistry and Oral and Maxillofacial Surgery.", Medicina (Kaunas, Lithuania), 2022;58(8).
- B. Feher, U. Kuchler, F. Schwendicke, L. Schneider, J. de Grano Cejudo Oro, T. Xi, S. Vinayahalingam, T. Hsu, J. Brinz, A. Chaurasia, K. Dhingra, R. Gaudin, H. Mohammad-Rahimi, N. Pereira, F. Perez-Pastor, O. Tryfonos, S. Uribe, M. Hanisch and J. Krois, "Emulating Clinical Diagnostic Reasoning for Jaw Cysts with Machine Learning.", Diagnostics (Basel, Switzerland), 2022;12(8).
- N. Harlianto, J. Westerink, M. Hol, R. Wittenberg, W. Foppen, P. van der Veen, B. van Ginneken, J. Verlaan, P. de Jong, F. Mohamed Hoesein and UCC-SMART Study Group , "Patients with diffuse idiopathic skeletal hyperostosis have an increased burden of thoracic aortic calcifications", Rheumatology Advances in Practice, 2022;6(2):rkac060.
- N. Naik, B. Hameed, N. Sooriyaperakasam, S. Vinayahalingam, V. Patil, K. Smriti, J. Saxena, M. Shah, S. Ibrahim, A. Singh, H. Karimi, K. Naganathan, D. Shetty, B. Rai, P. Chlosta and B. Somani, "Transforming healthcare through a digital revolution: A review of digital healthcare technologies and solutions.", Frontiers in digital health, 2022;4:919985.
- E. Munari, G. Querzoli, M. Brunelli, M. Marconi, M. Sommaggio, M. Cocchi, G. Martignoni, G. Netto, A. Caliò, L. Quatrini, F. Mariotti, C. Luchini, I. Girolami, A. Eccher, D. Segala, F. Ciompi, G. Zamboni, L. Moretta and G. Bogina, "Comparison of three validated PD-L1 immunohistochemical assays in urothelial carcinoma of the bladder: interchangeability and issues related to patient selection.", Frontiers in immunology, 2022;13:954910.
- R. Vliegenthart, A. Fouras, C. Jacobs and N. Papanikolaou, "Innovations in thoracic imaging: CT, radiomics, AI and x-ray velocimetry", Respirology, 2022;27(10):818-833.
- E. Calli, K. Murphy, E. Scholten, S. Schalekamp and B. van Ginneken, "Explainable emphysema detection on chest radiographs with deep learning", PLoS One, 2022;17(7):e0267539.
- N. Marini, S. Marchesin, S. Otálora, M. Wodzinski, A. Caputo, M. van Rijthoven, W. Aswolinskiy, J. Bokhorst, D. Podareanu, E. Petters, S. Boytcheva, G. Buttafuoco, S. Vatrano, F. Fraggetta, J. van der Laak, M. Agosti, F. Ciompi, G. Silvello, H. Muller and M. Atzori, "Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations.", NPJ digital medicine, 2022;5(1):102.
- M. Hermsen, F. Ciompi, A. Adefidipe, A. Denic, A. Dendooven, B. Smith, D. van Midden, J. Brasen, J. Kers, M. Stegall, P. Bándi, T. Nguyen, Z. Swiderska-Chadaj, B. Smeets, L. Hilbrands and J. van der Laak, "Convolutional neural networks for the evaluation of chronic and inflammatory lesions in kidney transplant biopsies", American Journal of Pathology, 2022;192(10):1418-1432.
- L. Adams, M. Makowski, G. Engel, M. Rattunde, F. Busch, P. Asbach, S. Niehues, S. Vinayahalingam, B. van Ginneken, G. Litjens and K. Bressem, "Prostate158 - An expert-annotated 3T MRI dataset and algorithm for prostate cancer detection.", Computers in biology and medicine, 2022;148:105817.
- M. Antonelli, A. Reinke, S. Bakas, K. Farahani, A. Kopp-Schneider, B. Landman, G. Litjens, B. Menze, O. Ronneberger, R. Summers, B. van Ginneken, M. Bilello, P. Bilic, P. Christ, R. Do, M. Gollub, S. Heckers, H. Huisman, W. Jarnagin, M. McHugo, S. Napel, J. Pernicka, K. Rhode, C. Tobon-Gomez, E. Vorontsov, J. Meakin, S. Ourselin, M. Wiesenfarth, P. Arbelaez, B. Bae, S. Chen, L. Daza, J. Feng, B. He, F. Isensee, Y. Ji, F. Jia, I. Kim, K. Maier-Hein, D. Merhof, A. Pai, B. Park, M. Perslev, R. Rezaiifar, O. Rippel, I. Sarasua, W. Shen, J. Son, C. Wachinger, L. Wang, Y. Wang, Y. Xia, D. Xu, Z. Xu, Y. Zheng, A. Simpson, L. Maier-Hein and M. Cardoso, "The Medical Segmentation Decathlon", Nature Communications, 2022;13(1):4128.
- G. Litjens, F. Ciompi and J. van der Laak, "A Decade of GigaScience: The Challenges of Gigapixel Pathology Images.", GigaScience, 2022;11.
- H. Pinckaers, J. van Ipenburg, J. Melamed, A. De Marzo, E. Platz, B. van Ginneken, J. van der Laak and G. Litjens, "Predicting biochemical recurrence of prostate cancer with artificial intelligence", Communications Medicine, 2022;2:64.
- K. Koschmieder, M. Paul, T. van den Heuvel, A. van der Eerden, B. van Ginneken and R. Manniesing, "Automated detection of cerebral microbleeds via segmentation in susceptibility-weighted images of patients with traumatic brain injury", NeuroImage: Clinical, 2022;35:103027.
- C. de Vente, L. Boulogne, K. Venkadesh, C. Sital, N. Lessmann, C. Jacobs, C. Sánchez and B. van Ginneken, "Automated COVID-19 Grading with Convolutional Neural Networks in Computed Tomography Scans: A Systematic Comparison", IEEE Transactions on Artificial Intelligence, 2022;3(2):129-138.
- I. Girolami, L. Pantanowitz, S. Marletta, M. Hermsen, J. van der Laak, E. Munari, L. Furian, F. Vistoli, G. Zaza, M. Cardillo, L. Gesualdo, G. Gambaro and A. Eccher, "Artificial intelligence applications for pre-implantation kidney biopsy pathology practice: a systematic review.", Journal of nephrology, 2022.
- E. Sogancioglu, K. Murphy, E. Th Scholten, L. Boulogne, M. Prokop and B. van Ginneken, "Automated estimation of total lung volume using chest radiographs and deep learning", Medical Physics, 2022;49(7):4466-4477.
- S. Satturwar, I. Girolami, E. Munari, F. Ciompi, A. Eccher and L. Pantanowitz, "Program death ligand-1 immunocytochemistry in lung cancer cytological samples: A systematic review.", Diagnostic cytopathology, 2022;50(6):313-323.
- Y. Chen, S. Vinayahalingam, S. Bergé, Y. Liao, T. Maal and T. Xi, "Is the pattern of mandibular asymmetry in mild craniofacial microsomia comparable to non-syndromic class II asymmetry?", Clinical oral investigations, 2022;26(6):4603-4613.
- L. Bohner, S. Vinayahalingam, J. Kleinheinz and M. Hanisch, "Digital Implant Planning in Patients with Ectodermal Dysplasia: Clinical Report.", International journal of environmental research and public health, 2022;19(3).
- M. Schilpzand, C. Neff, J. van Dillen, B. van Ginneken, T. Heskes, C. de Korte and T. van den Heuvel, "Automatic Placenta Localization From Ultrasound Imaging in a Resource-Limited Setting Using a Predefined Ultrasound Acquisition Protocol and Deep Learning.", Ultrasound in medicine & biology, 2022;48(4):663-674.
- W. Bulten, K. Kartasalo, P. Chen, P. Strom, H. Pinckaers, K. Nagpal, Y. Cai, D. Steiner, H. van Boven, R. Vink, C. de Hulsbergen-van Kaa, J. van der Laak, M. Amin, A. Evans, T. van der Kwast, R. Allan, P. Humphrey, H. Gronberg, H. Samaratunga, B. Delahunt, T. Tsuzuki, T. Hakkinen, L. Egevad, M. Demkin, S. Dane, F. Tan, M. Valkonen, G. Corrado, L. Peng, C. Mermel, P. Ruusuvuori, G. Litjens, M. Eklund, A. Brilhante, A. Cakir, X. Farre, K. Geronatsiou, V. Molinie, G. Pereira, P. Roy, G. Saile, P. Salles, E. Schaafsma, J. Tschui, J. Billoch-Lima, E. Pereira, M. Zhou, S. He, S. Song, Q. Sun, H. Yoshihara, T. Yamaguchi, K. Ono, T. Shen, J. Ji, A. Roussel, K. Zhou, T. Chai, N. Weng, D. Grechka, M. Shugaev, R. Kiminya, V. Kovalev, D. Voynov, V. Malyshev, E. Lapo, M. Campos, N. Ota, S. Yamaoka, Y. Fujimoto, K. Yoshioka, J. Juvonen, M. Tukiainen, A. Karlsson, R. Guo, C. Hsieh, I. Zubarev, H. Bukhar, W. Li, J. Li, W. Speier, C. Arnold, K. Kim, B. Bae, Y. Kim, H. Lee, J. Park and the PANDA challenge consortium, "Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge", Nature Medicine, 2022.
- A. Schreuder, C. Jacobs, N. Lessmann, M. Broeders, M. Silva, I. Isgum, P. de Jong, M. van den Heuvel, N. Sverzellati, M. Prokop, U. Pastorino, C. Schaefer-Prokop and B. van Ginneken, "Scan-based competing death risk model for reevaluating lung cancer computed tomography screening eligibility", European Respiratory Journal, 2022;59(5):2101613.
- K. van Leeuwen, M. de Rooij, S. Schalekamp, B. van Ginneken and M. Rutten, "How does artificial intelligence in radiology improve efficiency and health outcomes?", Pediatric Radiology, 2022;52(11):2087-2093.
- M. den Van Bempt, S. Vinayahalingam, M. Han, S. Bergé and T. Xi, "The role of muscular traction in the occurrence of skeletal relapse after advancement bilateral sagittal split osteotomy (BSSO): A systematic review.", Orthodontics & craniofacial research, 2022;25(1):1-13.
- B. van Ginneken, "Tuberculosis Detection from Chest Radiographs: Stop Training Radiologists Now", Radiology, 2022;00:1-2.
- N. Alves, M. Schuurmans, G. Litjens, J. Bosma, J. Hermans and H. Huisman, "Fully Automatic Deep Learning Framework for Pancreatic Ductal Adenocarcinoma Detection on Computed Tomography", Cancers, 2022:376.
- S. Labus, M. Altmann, H. Huisman, A. Tong, T. Penzkofer, M. Choi, I. Shabunin, D. Winkel, P. Xinga, D. Szolar, S. Shea, R. Grimm, H. von Busch, A. Kamen, T. Herold and C. Baumann, "A concurrent, deep learning-based computer-aided detection system for prostate multiparametric MRI: a performance study involving experienced and less-experienced radiologists", European Radiology, 2022.
- M. Schaap, N. Cardozo, A. Patel, E. de Jong, B. van Ginneken and M. Seyger, "Image-based automated Psoriasis Area Severity Index scoring by Convolutional Neural Networks", Journal of the European Academy of Dermatology and Venereology, 2022;36(1):68-75.
- J. Bleker, T. Kwee, D. Rouw, C. Roest, J. Borstlap, I. de Jong, R. Dierckx, H. Huisman and D. Yakar, "A deep learning masked segmentation alternative to manual segmentation in biparametric MRI prostate cancer radiomics", European Radiology, 2022:1-10.
- M. Schuurmans, N. Alvás, P. Vendittelli, H. Huisman and J. Hermans, "Setting the Research Agenda for Clinical Artificial Intelligence in Pancreatic Adenocarcinoma Imaging", Cancers, 2022:3498.
- J. Noothout, N. Lessmann, M. Eede, L. van Harten, E. Sogancioglu, F. Heslinga, M. Veta, B. van Ginneken and I. Isgum, "Knowledge distillation with ensembles of convolutional neural networks for medical image segmentation", Journal of Medical Imaging, 2022.
- M. D'Amato, P. Szostak and B. Torben-Nielsen, "A Comparison Between Single- and Multi-Scale Approaches for Classification of Histopathology Images", Frontiers in Public Health, 2022;10.
- S. Schalekamp, W. Klein and K. van Leeuwen, "Current and emerging artificial intelligence applications in chest imaging: a pediatric perspective", Pediatric Radiology, 2022;52(11):2120-2130.
- M. Huisman and N. Lessmann, "Automatic Brand Identification of Orthopedic Implants from Radiographs: Ready for the Next Step?", Radiology: Artificial Intelligence, 2022;4(2):e220008.
- C. Roest, T. Kwee, A. Saha, J. Futterer, D. Yakar and H. Huisman, "AI-Assisted Biparametric MRI Surveillance of Prostate Cancer: Feasibility Study", European Radiology, 2022.
- L. Hadjiiski, K. Cha, H. Chan, K. Drukker, L. Morra, J. Näppi, B. Sahiner, H. Yoshida, Q. Chen, T. Deserno, H. Greenspan, H. Huisman, Z. Huo, R. Mazurchuk, N. Petrick, D. Regge, R. Samala, R. Summers, K. Suzuki, G. Tourassi, D. Vergara and S. III, "AAPM task group report 273: Recommendations on best practices for AI and machine learning for computer-aided diagnosis in medical imaging", Medical Physics, 2022.
- M. Sunoqrot, A. Saha, M. Hosseinzadeh, M. Elschot and H. Huisman, "Artificial Intelligence for Prostate MRI: Open Datasets, Available Applications, and Grand Challenges", European Radiology Experimental, 2022:35.
Papers in conference proceedings
- N. Alves and B. de Wilde, "Uncertainty-Guided Self-learning Framework for Semi-supervised Multi-organ Segmentation", Fast and Low-Resource Semi-supervised Abdominal Organ Segmentation, 2022:116-127.
- E. Chelebian and F. Ciompi, "Seeded iterative clustering for histology region identification", Learning Meaningful Representations of Life, NeurIPS 2022, 2022.
- L. Studer, J. Bokhorst, F. Ciompi, A. Fischer and H. Dawson, "Building-T-cell score is a potential predictor for more aggressive treatment in pT1 colorectal cancers", Proceedings of the ECDP 2022 18th European Congress on Digital Pathology, 2022.
Abstracts
- M. Schuurmans, N. Alves, H. Huisman and J. Hermans, "Deep Learning for Detection of Iso-attenuating Pancreatic Adenocarcinoma in Computed Tomography", Annual Meeting of the Radiological Society of North America, 2022.
- M. Grauw and B. Ginneken, "Semi-supervised 3D universal lesion segmentation in CT thorax-abdomen scans", European Congress of Radiology, 2022.
- A. Saha, J. Bosma, J. Twilt, B. van Ginneken, D. Yakar, M. Elschot, J. Veltman, J. Futterer, M. de Rooij and H. Huisman, "Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI: The PI-CAI Challenge", Annual Meeting of the Radiological Society of North America, 2022.
- M. Grauw, B. Ginneken, B. Geisler, E. Smit, M. Rooij, S. Schalekamp and M. Prokop, "Deep learning universal lesion segmentation for automated RECIST measurements on CT: comparison to manual assessment by radiologists", European Congress of Radiology, 2022.
- S. Fransen, C. Roest, Q. van Lohuizen, J. Bosma, 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, 2022.
- L. Deden, K. van Leeuwen, M. Becks, M. Bernsen, M. de Rooij, J. Martens and F. Meijer, "Gluren bij de buren - Evaluating and sharing real-world experience of an AI stroke tool in two centres", Radiologendagen, 2022.
- K. van Leeuwen, M. de Rooij, S. Schalekamp, B. van Ginneken and M. Rutten, "The rise of artificial intelligence solutions in radiology departments in the Netherlands", European Congress of Radiology, 2022.
- I. van den Berk, C. Jacobs, M. Kanglie, O. Mets, M. Snoeren, A. van Montauban Swijndregt, E. Taal, T. van Engelen, J. Prins, S. Bipat, P. Bossuyt and J. Stoker, "Added value of artificial intelligence for the detection and analysis of lung nodules on ultra-low-dose CT in an emergency setting", Annual Meeting of the Radiological Society of North America, 2022.
- K. Venkadesh, T. Aleef, A. Schreuder, E. Scholten, B. van Ginneken, M. Prokop and C. Jacobs, "Deep learning for estimating pulmonary nodule malignancy risk using prior CT examinations in lung cancer screening", European Congress of Radiology, 2022.
- L. van Eekelen, E. Munari, L. Meesters, G. de Souza, M. Demirel-Andishmand, D. Zegers, M. Looijen-Salamon, S. Vos and F. Ciompi, "Nuclei detection with YOLOv5 in PD-L1 stained non-small cell lung cancer whole slide images", European Congress of Pathology, 2022.
- E. van Genugten, B. Piet, G. Schreibelt, T. van Oorschot, G. van den Heuvel, F. Ciompi, C. Jacobs, J. de Vries, M. van den Heuvel and E. Aarntzen, "Imaging tumor-infiltrating CD8 (+) T-cells in non-small cell lung cancer patients upon neo-adjuvant treatment with durvalumab", European Molecular Imaging Meeting, 2022.
- L. Boulogne and B. van Ginneken, "Automatically Generated CT Severity Scores for COVID-19 Predict Death or Intubation at 1-Month Follow-Up", Annual Meeting of the Radiological Society of North America, 2022.
- N. Alves, J. Bosma and H. Huisman, "Towards Safe Clinical Use of Artificial Intelligence for Cancer Detection Through Uncertainty Quantification", Annual Meeting of the Radiological Society of North America, 2022.
- C. Roest, T. Kwee, A. Saha, J. Futterer, D. Yakar and H. Huisman, "AI-Assisted Biparametric MRI Surveillance of Prostate Cancer: Feasibility Study", European Congress of Radiology, 2022.
- K. van Leeuwen, M. Becks, S. Schalekamp, B. van Ginneken, M. Rutten, M. de Rooij and F. Meijer, "Real-world evaluation of artificial intelligence software for cerebral large vessel occlusion detection in CT angiography", European Congress of Radiology, 2022.
- T. Perik, J. Hermans and H. Huisman, "AI-assisted analysis of CT perfusion to predict response in patients with pancreatic adenocarcinoma", European Congress of Radiology, 2022.
- J. van der Graaf, M. van Hooff, C. Buckens and N. Lessmann, "Segmentation of vertebrae and intervertebral discs in lumbar spine MR images with iterative instance segmentation", Medical Imaging 2022: Image Processing, 2022;12032:909-913.
- S. de Jong, N. Alves, M. Schuurmans, J. Hermans and H. Huisman, "Deep Learning for Automatic Contrast Enhancement Phase Detection on Abdominal Computed Tomography", Annual Meeting of the Radiological Society of North America, 2022.
- J. Spronck, L. Eekelen, L. Tessier, J. Bogaerts, L. van der Woude, M. van den Heuvel, W. Theelen and F. Ciompi, "Deep learning-based quantification of immune infiltrate for predicting response to pembrolizumab from pre-treatment biopsies of metastatic non-small cell lung cancer: A study on the PEMBRO-RT phase II trial", Immuno-Oncology and Technology, 2022.
- L. van Eekelen, E. Munari, I. Girolami, A. Eccher, J. van der Laak, K. Grünberg, M. Looijen-Salamon, S. Vos and F. Ciompi, "Inter-rater agreement of pathologists on determining PD-L1 status in non-small cell lung cancer", European Congress of Pathology, 2022.
PhD theses
- G. Chlebus, "Deep Learning-Based Segmentation in Multimodal Abdominal Imaging", PhD thesis, 2022.
- A. Hering, "Deep-Learning-Based Image Registration and Tumor Follow-Up Analysis", PhD thesis, 2022.
- B. Liefers, "Deep Learning Algorithms for Age-Related Macular Degeneration", PhD thesis, 2022.
- W. Bulten, "Artificial intelligence as a digital fellow in pathology: Human-machine synergy for improved prostate cancer diagnosis", PhD thesis, 2022.
Master theses
- S. Vyawahare, "Automated Cephalometric Analysis on Lateral Headplates for Orthodontic Diagnosis", Master thesis, 2022.
- M. Botros, "Automated Detection and Assessment of Vertebral Fractures in CT Images", Master thesis, 2022.
- A. Archit and B. van Ginneken, "Automated Abdominal Aortic Aneurysm Detection on CT Scans", Master thesis, 2022.
- S. Adilina, A. Saha and H. Huisman, "Domain Generalization for Prostate Cancer Detection in MRI", Master thesis, 2022.