Detection of reticular pseudodrusen on optical coherence tomography images
Elsawy A, Keenan T, Agron E, Chen Q, Chew E, Lu Z. Detection of reticular pseudodrusen on optical coherence tomography images. Progress In Biomedical Optics And Imaging 2024, 12926: 1292632-1292632-5. DOI: 10.1117/12.3007014.Peer-Reviewed Original ResearchAge-related macular degenerationSD-OCT scansAge-Related Eye Disease Study 2Detect reticular pseudodrusenReticular pseudodrusenSD-OCTFundus autofluorescenceVolumetric spectral-domain optical coherence tomographySpectral-domain optical coherence tomographySubretinal drusenoid depositsOptical coherence tomography imagesPredictors of progressionOptical coherence tomographyReceiver characteristic operating curvesDrusenoid depositsMacular degenerationOCT studiesCoherence tomographyDisease featuresTomography imagesOperating curvePseudodrusenAge-relatedClassification networkMulti-taskingAssessing Neural Network Representations During Training Using Noise-Resilient Diffusion Spectral Entropy
Liao D, Liu C, Christensen B, Tong A, Huguet G, Wolf G, Nickel M, Adelstein I, Krishnaswamy S. Assessing Neural Network Representations During Training Using Noise-Resilient Diffusion Spectral Entropy. 2024, 00: 1-6. DOI: 10.1109/ciss59072.2024.10480166.Peer-Reviewed Original ResearchMutual information neural estimatorMutual informationHigh-dimensional simulation dataHigh-dimensional dataNeural network representationSpectral entropyCIFAR-10Information-theoretic measuresClass labelsSTL-10Classification networkNeural representationSelf-supervisionSupervised learningIntrinsic dimensionalityClassification accuracyNeural networkAmbient dimensionNoise-resilientNeural estimatorNetwork initializationData geometryNetwork representationOverfittingNetwork
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply