Generative Adversarial Networks for Cell Segmentation in Human Corneal Endothelium-Reference-Cited by-同舟云学术

Generative Adversarial Networks for Cell Segmentation in Human Corneal Endothelium

Published:2022 Issue: Volume: Page:
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Container-title:Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP)
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Author:

Mendoza Kevin D.,Sierra Juan S.,Tello Alejandro,Galvis Virgilio,Romero Lenny A.,Marrugo Andrés G.

Abstract

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.

Publisher

Optica Publishing Group

Reference6 articles.

1. Cellular membrane activity in the corneal endothelium of the intact eye

2. Development of a Reliable Automated Algorithm for the Morphometric Analysis of Human Corneal Endothelium

3. Deep Learning as a Tool for Automatic Segmentation of Corneal Endothelium Images

4. Automated corneal endothelium image segmentation in the presence of cornea guttata via convolutional neural networks;Sierra,2020

5. Generating density maps for convolutional neural network-based cell counting in specular microscopy images;Sierra,2020

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