Using spatial-temporal ensembles of convolutional neural networks for lumen segmentation in ureteroscopy

PURPOSE: Ureteroscopy is an efficient endoscopic minimally invasive technique for the diagnosis and treatment of upper tract urothelial carcinoma. During ureteroscopy, the automatic segmentation of the hollow lumen is of primary importance, since it indicates the path that the endoscope should follo...

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Detalles Bibliográficos
Autores principales: Lazo, Jorge F., Marzullo, Aldo, Moccia, Sara, Catellani, Michele, Rosa, Benoit, de Mathelin, Michel, De Momi, Elena
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8166718/
https://www.ncbi.nlm.nih.gov/pubmed/33909264
http://dx.doi.org/10.1007/s11548-021-02376-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8166718/
https://www.ncbi.nlm.nih.gov/pubmed/33909264
http://dx.doi.org/10.1007/s11548-021-02376-3

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