Publications of Bram van Ginneken
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. Lohofer, 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. Lipkova, M. Rempfler, M. Piraud, J. Kirschke, B. Wiestler, Z. Zhang, C. Hulsemeyer, 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. Giro-i-Nieto, F. Gruen, X. Han, P. Heng, J. Hesser, J. Moltz, C. Igel, F. Isensee, P. Jager, 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.
- 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. Troltzsch, M. Heiland, T. Flugge 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- G. Chlebus, A. Schenk, H. Hahn, B. Van Ginneken and H. Meine, "Robust Segmentation Models Using an Uncertainty Slice Sampling-Based Annotation Workflow", IEEE Access, 2022;10:4728-4738.
- 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. 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.
- B. van Ginneken, "Tuberculosis Detection from Chest Radiographs: Stop Training Radiologists Now", Radiology, 2022;00:1-2.
Abstracts
- 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.
- 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.
- A. Saha, J.S. 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 and B. Ginneken, "Semi-supervised 3D universal lesion segmentation in CT thorax-abdomen scans", European Congress of Radiology, 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.
- 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.
- 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.
PhD theses
- B. Liefers, "Deep Learning Algorithms for Age-Related Macular Degeneration", PhD thesis, 2022.
- G. Chlebus, "Deep Learning-Based Segmentation in Multimodal Abdominal Imaging", PhD thesis, 2022.
- W. Bulten, "Artificial intelligence as a digital fellow in pathology: Human-machine synergy for improved prostate cancer diagnosis", PhD thesis, 2022.
- A. Hering, "Deep-Learning-Based Image Registration and Tumor Follow-Up Analysis", PhD thesis, 2022.
Master theses
- A. Archit and B. van Ginneken, "Automated Abdominal Aortic Aneurysm Detection on CT Scans", Master thesis, 2022.