Standardised lesion segmentation for imaging biomarker quantitation: a consensus recommendation from ESR and EORTC

BACKGROUND: Lesion/tissue segmentation on digital medical images enables biomarker extraction, image-guided therapy delivery, treatment response measurement, and training/validation for developing artificial intelligence algorithms and workflows. To ensure data reproducibility, criteria for standard...

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Detalles Bibliográficos
Autores principales: deSouza, Nandita M., van der Lugt, Aad, Deroose, Christophe M., Alberich-Bayarri, Angel, Bidaut, Luc, Fournier, Laure, Costaridou, Lena, Oprea-Lager, Daniela E., Kotter, Elmar, Smits, Marion, Mayerhoefer, Marius E., Boellaard, Ronald, Caroli, Anna, de Geus-Oei, Lioe-Fee, Kunz, Wolfgang G., Oei, Edwin H., Lecouvet, Frederic, Franca, Manuela, Loewe, Christian, Lopci, Egesta, Caramella, Caroline, Persson, Anders, Golay, Xavier, Dewey, Marc, O’Connor, James P. B., deGraaf, Pim, Gatidis, Sergios, Zahlmann, Gudrun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Vienna 2022
Materias:
Guideline
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9532485/
https://www.ncbi.nlm.nih.gov/pubmed/36194301
http://dx.doi.org/10.1186/s13244-022-01287-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9532485/
https://www.ncbi.nlm.nih.gov/pubmed/36194301
http://dx.doi.org/10.1186/s13244-022-01287-4

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