2D and 3D convolutional neural networks for outcome modelling of locally advanced head and neck squamous cell carcinoma

For treatment individualisation of patients with locally advanced head and neck squamous cell carcinoma (HNSCC) treated with primary radiochemotherapy, we explored the capabilities of different deep learning approaches for predicting loco-regional tumour control (LRC) from treatment-planning compute...

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Detalles Bibliográficos
Autores principales: Starke, Sebastian, Leger, Stefan, Zwanenburg, Alex, Leger, Karoline, Lohaus, Fabian, Linge, Annett, Schreiber, Andreas, Kalinauskaite, Goda, Tinhofer, Inge, Guberina, Nika, Guberina, Maja, Balermpas, Panagiotis, von der Grün, Jens, Ganswindt, Ute, Belka, Claus, Peeken, Jan C., Combs, Stephanie E., Boeke, Simon, Zips, Daniel, Richter, Christian, Troost, Esther G. C., Krause, Mechthild, Baumann, Michael, Löck, Steffen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7518264/
https://www.ncbi.nlm.nih.gov/pubmed/32973220
http://dx.doi.org/10.1038/s41598-020-70542-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7518264/
https://www.ncbi.nlm.nih.gov/pubmed/32973220
http://dx.doi.org/10.1038/s41598-020-70542-9

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