Comparing the Clinical Viability of Automated Fundus Image Segmentation Methods

Recent methods for automatic blood vessel segmentation from fundus images have been commonly implemented as convolutional neural networks. While these networks report high values for objective metrics, the clinical viability of recovered segmentation masks remains unexplored. In this paper, we perfo...

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Detalles Bibliográficos
Autores principales: Gojić, Gorana, Petrović, Veljko B., Dragan, Dinu, Gajić, Dušan B., Mišković, Dragiša, Džinić, Vladislav, Grgić, Zorka, Pantelić, Jelica, Oros, Ana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9735987/
https://www.ncbi.nlm.nih.gov/pubmed/36501801
http://dx.doi.org/10.3390/s22239101

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9735987/
https://www.ncbi.nlm.nih.gov/pubmed/36501801
http://dx.doi.org/10.3390/s22239101

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