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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. Berge 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.
J. van der Laak, K. Grünberg, A. Frisk and P. Moulin, "BUILDING AN E.U.-SCALE DIGITAL PATHOLOGY REPOSITORY: THE BIGPICTURE INITIATIVE",
Journal of Pathology Informatics,
2022;13:100026.
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.
N. Alves, M. Schuurmans, G. Litjens, J.S. Bosma, J. Hermans and H. Huisman, "Fully Automatic Deep Learning Framework for Pancreatic Ductal Adenocarcinoma Detection on Computed Tomography",
Cancers,
2022:376.
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.
L. Hadjiiski, K. Cha, H. Chan, K. Drukker, L. Morra, J. Nappi, 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. Huisman and N. Lessmann, "Automatic Brand Identification of Orthopedic Implants from Radiographs: Ready for the Next Step?",
Radiology: Artificial Intelligence,
2022;4(2):e220008.
M. Schuurmans, N. Alves, P. Vendittelli, H. Huisman and J. Hermans, "Setting the Research Agenda for Clinical Artificial Intelligence in Pancreatic Adenocarcinoma Imaging",
Cancers,
2022:3498.
S. Otálora, N. Marini, D. Podareanu, R. Hekster, D. Tellez, J. Der Van Laak, H. Müller and M. Atzori, "stainlib: a python library for augmentation and normalization of histopathology H&E images",
Preprint,
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 Radiology,
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.
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. 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.
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.
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. Eisenmann, A. Reinke, V. Weru, M. Tizabi, F. Isensee, T. Adler, P. Godau, V. Cheplygina, M. Kozubek, S. Ali, A. Gupta, J. Kybic, A. Noble, C. de Solórzano, S. Pachade, C. Petitjean, D. Sage, D. Wei, E. Wilden, D. Alapatt, V. Andrearczyk, U. Baid, S. Bakas, N. Balu, S. Bano, V. Bawa, J. Bernal, S. Bodenstedt, A. Casella, J. Choi, O. Commowick, M. Daum, A. Depeursinge, R. Dorent, J. Egger, H. Eichhorn, S. Engelhardt, M. Ganz, G. Girard, L. Hansen, M. Heinrich, N. Heller, A. Hering, A. Huaulmé, H. Kim, B. Landman, H. Li, J. Li, J. Ma, A. Martel, C. Martín-Isla, B. Menze, C. Nwoye, V. Oreiller, N. Padoy, S. Pati, K. Payette, C. Sudre, K. van Wijnen, A. Vardazaryan, T. Vercauteren, M. Wagner, C. Wang, M. Yap, Z. Yu, C. Yuan, M. Zenk, A. Zia, D. Zimmerer, R. Bao, C. Choi, A. Cohen, O. Dzyubachyk, A. Galdran, T. Gan, T. Guo, P. Gupta, M. Haithami, E. Ho, I. Jang, Z. Li, Z. Luo, F. Lux, S. Makrogiannis, D. Müller, Y. Oh, S. Pang, C. Pape, G. Polat, C. Reed, K. Ryu, T. Scherr, V. Thambawita, H. Wang, X. Wang, K. Xu, H. Yeh, D. Yeo, Y. Yuan, Y. Zeng, X. Zhao, J. Abbing, J. Adam, N. Adluru, N. Agethen, S. Ahmed, Y. Khalil, M. Alenyà, E. Alhoniemi, C. An, T. Anwar, T. Arega, N. Avisdris, D. Aydogan, Y. Bai, M. Calisto, B. Basaran, M. Beetz, C. Bian, H. Bian, K. Blansit, L. Bloch, R. Bohnsack, S. Bosticardo, J. Breen, M. Brudfors, R. Brüngel, M. Cabezas, A. Cacciola, Z. Chen, Y. Chen, D. Chen, M. Cho, M. Choi, C. Xie, D. Cobzas, J. Cohen-Adad, J. Acero, S. Das, M. de Oliveira, H. Deng, G. Dong, L. Doorenbos, C. Efird, S. Escalera, D. Fan, M. Serj, A. Fenneteau, L. Fidon, P. Filipiak, R. Finzel, N. Freitas, C. Friedrich, M. Fulton, F. Gaida, F. Galati, C. Galazis, C. Gan, Z. Gao, S. Gao, M. Gazda, B. Gerats, N. Getty, A. Gibicar, R. Gifford, S. Gohil, M. Grammatikopoulou, D. Grzech, O. Güley, T. Günnemann, C. Guo, S. Guy, H. Ha, L. Han, I. Han, A. Hatamizadeh, T. He, J. Heo, S. Hitziger, S. Hong, S. Hong, R. Huang, Z. Huang, M. Huellebrand, S. Huschauer, M. Hussain, T. Inubushi, E. Polat, M. Jafaritadi, S. Jeong, B. Jian, Y. Jiang, Z. Jiang, Y. Jin, S. Joshi, A. Kadkhodamohammadi, R. Kamraoui, I. Kang, J. Kang, D. Karimi, A. Khademi, M. Khan, S. Khan, R. Khantwal, K. Kim, T. Kline, S. Kondo, E. Kontio, A. Krenzer, A. Kroviakov, H. Kuijf, S. Kumar, F. La Rosa, A. Lad, D. Lee, M. Lee, C. Lena, H. Li, L. Li, X. Li, F. Liao, K. Liao, A. Oliveira, C. Lin, S. Lin, A. Linardos, M. Linguraru, H. Liu, T. Liu, D. Liu, Y. Liu, J. Lourenço-Silva, J. Lu, J. Lu, I. Luengo, C. Lund, H. Luu, Y. Lv, Y. Lv, U. Macar, L. Maechler, S. L., K. Marshall, M. Mazher, R. McKinley, A. Medela, F. Meissen, M. Meng, D. Miller, S. Mirjahanmardi, A. Mishra, S. Mitha, H. Mohy-ud-Din, T. Mok, G. Murugesan, E. Karthik, S. Nalawade, J. Nalepa, M. Naser, R. Nateghi, H. Naveed, Q. Nguyen, C. Quoc, B. Nichyporuk, B. Oliveira, D. Owen, J. Pal, J. Pan, W. Pan, W. Pang, B. Park, V. Pawar, K. Pawar, M. Peven, L. Philipp, T. Pieciak, S. Plotka, M. Plutat, F. Pourakpour, D. Preloznik, K. Punithakumar, A. Qayyum, S. Queirós, A. Rahmim, S. Razavi, J. Ren, M. Rezaei, J. Rico, Z. Rieu, M. Rink, J. Roth, Y. Ruiz-Gonzalez, N. Saeed, A. Saha, M. Salem, R. Sanchez-Matilla, K. Schilling, W. Shao, Z. Shen, R. Shi, P. Shi, D. Sobotka, T. Soulier, B. Fadida, D. Stoyanov, T. Mun, X. Sun, R. Tao, F. Thaler, A. Théberge, F. Thielke, H. Torres, K. Wahid, J. Wang, Y. Wang, W. Wang, X. Wang, J. Wen, N. Wen, M. Wodzinski, Y. Wu, F. Xia, T. Xiang, C. Xiaofei, L. Xu, T. Xue, Y. Yang, L. Yang, K. Yao, H. Yao, A. Yazdani, M. Yip, H. Yoo, F. Yousefirizi, S. Yu, L. Yu, J. Zamora, R. Zeineldin, D. Zeng, J. Zhang, B. Zhang, J. Zhang, F. Zhang, H. Zhang, Z. Zhao, Z. Zhao, J. Zhao, C. Zhao, Q. Zheng, Y. Zhi, Z. Zhou, B. Zou, K. Maier-Hein, P. Jäger, A. Kopp-Schneider and L. Maier-Hein, "Biomedical image analysis competitions: The state of current participation practice",
arXiv:2212.08568,
2022.
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, F. Ciompi and C. Wählby, "Seeded iterative clustering for histology region identification",
Medical Imaging Meets NeurIPS Workshop - 36th Conference on Neural Information Processing Systems (NeurIPS),
2022.
Y. Li, Y. Fu, Q. Yang, Z. Min, W. Yan, H. Huisman, D. Barratt, V. Prisacariu and Y. Hu, "FEW-SHOT Image Segmentation for Cross-Institution Male Pelvic Organs Using Registration-Assisted Prototypical Learning",
2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI),
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.
M. van Bommel, J. Bogaerts, R. Hermens, M. Steenbeek, J. de Hullu, J. van der Laak and M. Simons, "2022-RA-646-ESGO Consensus based recommendations for the diagnosis of serous tubal intraepithelial carcinoma, an international delphi study",
Pathology,
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.
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.
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.
L. van Eekelen, E. Munari, I. Girolami, A. Eccher, J. van der Laak, K. Grunberg, 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.
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.
N. Alves, J.S. 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.
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.
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.
M. van Rijssel, C. van den Berg, C. Noordman and A. van Lier, "Accelerating phase-cycled bSSFP using sparsity across the phase-cycling dimension",
ISMRM-ESMRMB,
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.
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.
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.
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.
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.
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.
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.
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.
J.S. Bosma, N. Alves and H. Huisman, "Performant and Reproducible Deep Learning Based Cancer Detection Models for Medical Imaging",
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.
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.
A. Hering, A. Lange, S. Heldmann, S. Häger and S. Kuckertz, "Fraunhofer MEVIS Image Registration Solutions for the Learn2Reg 2021 Challenge",
Biomedical Image Registration, Domain Generalisation and Out-of-Distribution Analysis,
2022:147-152.