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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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| Gepubliceerd in: | Int J Comput Assist Radiol Surg |
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| Hoofdauteurs: | , , , , , , |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
Springer International Publishing
2021
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| Onderwerpen: | |
| Online toegang: | 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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