Self-Supervised Deep-Learning Segmentation of Corneal Endothelium Specular Microscopy Images
Author:
Affiliation:
1. Universidad Tecnológica de Bolívar.,Facultad de Ingeniería.,Cartagena,Colombia
2. Centro Oftalmológico Virgilio Galvis Floridablanca,Colombia
3. Universidad Tecnológica de Bolívar,Facultad de Ciencias Básicas,Cartagena,Colombia
Funder
Ministerio de Ciencia, Tecnología e Innovacioón
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10225685/10225754/10226148.pdf?arnumber=10226148
Reference27 articles.
1. BT-Unet: A self-supervised learning framework for biomedical image segmentation using Barlow Twins with U-Net models;punn;Image and Video Processing,2022
2. Exploring Simple Siamese Representation Learning (Simsiam);chen;Computer Vision and Pattern Recognition,2020
3. DenseUNets with feedback non-local attention for the segmentation of specular microscopy images of the corneal endothelium with guttae;vigueras;Nature Scientific Reports,2022
Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Super resolution-based methodology for self-supervised segmentation of microscopy images;Frontiers in Microbiology;2024-03-12
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