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- W2901929328 abstract "Examination of the retina in Spectral-domain Optical Coherence Tomography for sight degrading diseases relies heavily on the extraction of the retinal layers to detect and quantify fluid structures. However, current methods of layer segmentation may perform poorly in the presence of heavy disease. Presented here is an automated method for retinal layer prediction, using cubic spline based interpolation, to compensate for potentially missing layer information. Simulated retinal layer segmentation error is used to validate this automated method, showing a high mean similarity between predicted and ground truth retinal layers of $0.9818 pm 0.0031$ based on the Jaccard Index." @default.
- W2901929328 created "2018-11-29" @default.
- W2901929328 creator A5037607172 @default.
- W2901929328 date "2017-10-01" @default.
- W2901929328 modified "2023-10-02" @default.
- W2901929328 title "Retinal Surface Prediction in Ophthalmic Spectral-Domain Optical Coherence Tomography" @default.
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- W2901929328 doi "https://doi.org/10.1109/nssmic.2017.8532819" @default.
- W2901929328 hasPublicationYear "2017" @default.
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