Generative Adversarial Networks for Cell Segmentation in Human Corneal Endothelium
We generate synthetic images with a generative adversarial network (GAN) model trained with image patches from specular microscopy corneal endothelial cells. Preliminary results show it may be a suitable approach for reliable cell segmentation. © 2022 The Author(s)
- Autores:
-
Mendoza, Kevin D.
Sierra, Juan S
Tello, Alejandro
Galvis, Virgilio
Romero, Lenny A.
Marrugo, Andrés G.
- Tipo de recurso:
- Fecha de publicación:
- 2022
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/12222
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/12222
https://scopus.utb.elogim.com/record/display.uri?eid=2-s2.0-85139550660&origin=resultslist&sort=plf-f&src=s&sid=95182a388077e068fee69a2cc90d4eed&sot=b&sdt=b&s=TITLE-ABS-KEY%28Generative+Adversarial+Networks+for+Cell+Segmentation+in+Human+Corneal+Endothelium%29&sl=97&sessionSearchId=95182a388077e068fee69a2cc90d4eed
- Palabra clave:
- Corneal Endothelium;
Hexagonal Cells;
Capillary Endothelial Cell
LEMB
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
| Summary: | We generate synthetic images with a generative adversarial network (GAN) model trained with image patches from specular microscopy corneal endothelial cells. Preliminary results show it may be a suitable approach for reliable cell segmentation. © 2022 The Author(s) |
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