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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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| Pubblicato in: | Int J Comput Assist Radiol Surg |
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| Autori principali: | , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Springer International Publishing
2021
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| Soggetti: | |
| Accesso online: | 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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