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...

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Detalles Bibliográficos
Autores principales: Negassi, Misgana, Suarez-Ibarrola, Rodrigo, Hein, Simon, Miernik, Arkadiusz, Reiterer, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Topic Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7508959/
https://www.ncbi.nlm.nih.gov/pubmed/31925551
http://dx.doi.org/10.1007/s00345-019-03059-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7508959/
https://www.ncbi.nlm.nih.gov/pubmed/31925551
http://dx.doi.org/10.1007/s00345-019-03059-0

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