An auxiliary diagnostic tool for common fundus diseases based on fundus color photography and light-weight classification models
Author:
Publisher
Springer Science and Business Media LLC
Subject
Cellular and Molecular Neuroscience,Sensory Systems,Ophthalmology
Link
https://link.springer.com/content/pdf/10.1007/s00417-023-06182-2.pdf
Reference20 articles.
1. Gulshan V, Peng L, Coram M et al (2016) Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. JAMA 316(22):2402–2410
2. Liu H, Li L, Wormstone IM et al (2019) Development and validation of a deep learning system to detect glaucomatous optic neuropathy using fundus photographs. JAMA Ophthalmol 137(12):1353–1360
3. Meng C, Yang D, Chen D (2021) Cerebral aneurysm image segmentation based on multi-modal convolutional neural network. Comput Methods Programs Biomed 208:106285
4. Zhu Q, Du B, Yan P (2020) Boundary-weighted domain adaptive neural network for prostate MR image segmentation. IEEE Trans Med Imaging 39(3):753–763
5. Karani N, Erdil E, Chaitanya K et al (2021) Test-time adaptable neural networks for robust medical image segmentation. Med Image Anal 68:101907
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