CA-GAN: A Method to Narrow Down Domain Differences of Retinal Fundus Images Caused by Camera Brands
Authors:
- 12 October 2023
- journal article
- research article
- Published by Springer Nature in Multimedia Tools and Applications
- Vol. 83 (14) , 42907-42928
Abstract
No abstract availableKeywords
Funding Information
- National Natural Science Foundation of China (61300098)
- Natural Science Foundation of Heilongjiang Province (F201347)
- Fundamental Research Funds for the Central Universities (2572015DY07)
- Harbin Science and Technology Bureau Manufacturing Innovation Talent Project (CXRC20221110393)
- Heilongjiang Science and Technology Department Provincial Key R&D Program Applied Research Project (SC2022ZX06C0025)
- Heilongjiang Science and Technology Department Provincial Key R&D Program Guidance Project (GZ20220088)
This publication has 34 references indexed in Scilit:
- End-to-End Adversarial Retinal Image SynthesisIEEE Transactions on Medical Imaging, 2017
- Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation2017
- Zoom-in-Net: Deep Mining Lesions for Diabetic Retinopathy Detection2017
- Deep image mining for diabetic retinopathy screeningMedical Image Analysis, 2017
- Image-to-Image Translation with Conditional Adversarial Networks2017
- Unsupervised Domain Adaptation in Brain Lesion Segmentation with Adversarial Networks2017
- Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus PhotographsJAMA, 2016
- Deep Residual Learning for Image Recognition2016
- Rethinking the Inception Architecture for Computer Vision2016
- DALSA: Domain Adaptation for Supervised Learning From Sparsely Annotated MR ImagesIEEE Transactions on Medical Imaging, 2015