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Identifying de novo Parkinson's disease with optical coherence tomography of the retina: A machine learning classification approach

Retinal layer thicknesses retrieved with different segmentation algorithms from optical coherence tomography scans acquired under different signal-to-noise ratio conditions

Testing a phantom eye under various signal-to-noise ratio conditions using eleven different OCT devices

Towards an accurate and robust retinal nerve fiber layer thickness assessment with OCT

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