Enhanced Visualization of Retinal Microvasculature in Optical Coherence Tomography Angiography Imaging via Deep Learning

Background: To investigate the effects of deep learning denoising on quantitative vascular measurements and the quality of optical coherence tomography angiography (OCTA) images. Methods: U-Net-based deep learning denoising with an averaged OCTA data set as teacher data was used in this study. One h...

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Detalles Bibliográficos
Autores principales: Kadomoto, Shin, Uji, Akihito, Muraoka, Yuki, Akagi, Tadamichi, Tsujikawa, Akitaka
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7290309/
https://www.ncbi.nlm.nih.gov/pubmed/32370282
http://dx.doi.org/10.3390/jcm9051322

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7290309/
https://www.ncbi.nlm.nih.gov/pubmed/32370282
http://dx.doi.org/10.3390/jcm9051322

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