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. Jarkman, M. Karlberg, M. Poceviciute, A. Boden, P. Bandi, G. Litjens, C. Lundstrom, 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. Polonia, 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. Muller, T. Primov, S. Vatrano and G. Silvello, "Empowering digital pathology applications through explainable knowledge extraction tools.",
Journal of pathology informatics,
2022;13:100139.
E. Munari, G. Querzoli, M. Brunelli, M. Marconi, M. Sommaggio, M. Cocchi, G. Martignoni, G. Netto, A. Calio, 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.
N. Marini, S. Marchesin, S. Otalora, 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.
J. Ogony, T. de Bel, D. Radisky, J. Kachergus, E. Thompson, A. Degnim, K. Ruddy, T. Hilton, M. Stallings-Mann, C. Vachon, T. Hoskin, M. Heckman, R. Vierkant, L. White, R. Moore, J. Carter, M. Jensen, L. Pacheco-Spann, J. Henry, A. Storniolo, S. Winham, J. van der Laak and M. Sherman, "Towards defining morphologic parameters of normal parous and nulliparous breast tissues by artificial intelligence",
Breast Cancer Research,
2022;24.
V. Bergshoeff, M. Balkenhol, A. Haesevoets, A. Ruland, M. Chenault, R. Nelissen, C. Peutz, R. Clarijs, J. der Van Laak, R. Takes, M. den Van Brekel, M. Van Velthuysen, F. Ramaekers, B. Kremer and E. Speel, "Evaluation Criteria for Chromosome Instability Detection by FISH to Predict Malignant Progression in Premalignant Glottic Laryngeal Lesions",
Cancers,
2022;14:3260.
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.
M. Sherman, T. de Bel, M. Heckman, L. White, J. Ogony, M. Stallings-Mann, T. Hilton, A. Degnim, R. Vierkant, T. Hoskin, M. Jensen, L. Pacheco-Spann, J. Henry, A. Storniolo, J. Carter, S. Winham, D. Radisky and J. van der Laak, "Serum hormone levels and normal breast histology among premenopausal women",
Breast Cancer Research and Treatment,
2022;194:149-158.
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.
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.
A. van der Kamp, T. Waterlander, T. de Bel, J. van der Laak, M. van den Heuvel-Eibrink, A. Mavinkurve-Groothuis and R. de Krijger, "Artificial Intelligence in Pediatric Pathology: The Extinction of a Medical Profession or the Key to a Bright Future?",
Pediatric and Developmental Pathology,
2022;25:380-387.
B. Sturm, D. Creytens, J. Smits, A. Ooms, E. Eijken, E. Kurpershoek, H. Küsters-Vandevelde, C. Wauters, W. Blokx and J. van der Laak, "Computer-Aided Assessment of Melanocytic Lesions by Means of a Mitosis Algorithm",
Diagnostics,
2022;12:436.
T. de Bel, G. Litjens, J. Ogony, M. Stallings-Mann, J. Carter, T. Hilton, D. Radisky, R. Vierkant, B. Broderick, T. Hoskin, S. Winham, M. Frost, D. Visscher, T. Allers, A. Degnim, M. Sherman and J. van der Laak, "Automated quantification of levels of breast terminal duct lobular (TDLU) involution using deep learning",
npj Breast Cancer,
2022;8.
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,
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L. Miesen, P. Bándi, B. Willemsen, F. Mooren, T. Strieder, E. Boldrini, V. Drenic, J. Eymael, R. Wetzels, J. Lotz, N. Weiss, E. Steenbergen, T. van Kuppevelt, M. van Erp, J. van der Laak, N. Endlich, M. Moeller, J. Wetzels, J. Jansen and B. Smeets, "Parietal epithelial cells maintain the epithelial cell continuum forming Bowman's space in focal segmental glomerulosclerosis",
Disease Models & Mechanisms,
2022;15.
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. 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.
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.
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.
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.
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.
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.
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.
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, 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.