Application of artificial neural networks for automated analysis of cystoscopic images: a review of the current status and future prospects

Background Optimal detection and surveillance of bladder cancer (BCa) rely primarily on the cystoscopic visualization of bladder lesions. AI-assisted cystoscopy may improve image recognition and accelerate data acquisition. Objective To provide a comprehensive review of machine learning (ML), deep l...

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Veröffentlicht in:	World journal of urology 2020-10, Vol.38 (10), p.2349-2358
Hauptverfasser:	Negassi, Misgana, Suarez-Ibarrola, Rodrigo, Hein, Simon, Miernik, Arkadiusz, Reiterer, Alexander
Format:	Artikel
Sprache:	eng
Schlagworte:	Bladder Bladder cancer Data acquisition Deep learning Medicine Medicine & Public Health Nephrology Neural networks Oncology Topic Paper Tumors Urology
Online-Zugang:	Volltext
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