Joint Motion Correction and 3D Segmentation with Graph-Assisted Neural Networks for Retinal OCT
Author:
Affiliation:
1. University of California,Department of Electrical and Computer Engineering,San Diego
2. Shiley Eye Institute University of California,Jacobs Retina Center,San Diego
Funder
National Eye Institute
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9897158/9897159/09898072.pdf?arnumber=9898072
Reference23 articles.
1. Deep learning based retinal OCT segmentation
2. Structured layer surface segmentation for retina OCT using fully convolutional regression networks
3. Quantitative Classification of Eyes with and without Intermediate Age-related Macular Degeneration Using Optical Coherence Tomography
4. Probabilistic intra-retinal layer segmentation in 3-D OCT images using global shape regularization
5. U-net: Convolutional networks for biomedical image segmentation;ronneberger;International Conference on Medical Image Computing and Computer-Assisted Intervention,2015
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. Retinal OCT Layer Segmentation via Joint Motion Correction and Graph-Assisted 3D Neural Network;IEEE Access;2023
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