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Is There More Than Meets the Eye?
How Electroretinogram Analysis adds a new Dimension to Retinal Diagnostics
Electroretinography (ERG) has been a cornerstone in ophthalmology and vision research for decades, enabling us to record the retina’s electrical activity in response to flashes of light. But the real question is: how can we uncover hidden clues in these complex waveforms to diagnose retinal diseases more accurately and earlier than ever before? A remarkable team of scientists from Russia, Korea, Germany, and Australia believes the answer may lie in a powerful collaboration between cutting-edge signal-processing tools and advanced machine learning. In their new study, they have shown that we can greatly enhance the diagnostic utility of ERG signals with a technique called the Short-Time Fourier Transform (STFT) combined with state-of-the-art deep learning architectures. Let us explore the details behind this interesting approach, why it is so timely, and how it could impact the future of retinal health care.
