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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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Dades bibliogràfiques
Publicat a:Int J Comput Assist Radiol Surg
Autors principals: Lazo, Jorge F., Marzullo, Aldo, Moccia, Sara, Catellani, Michele, Rosa, Benoit, de Mathelin, Michel, De Momi, Elena
Format: Artigo
Idioma:Inglês
Publicat: Springer International Publishing 2021
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Accés en línia:https://ncbi.nlm.nih.gov/pmc/articles/PMC8166718/
https://ncbi.nlm.nih.gov/pubmed/33909264
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s11548-021-02376-3
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