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AI spots neurons better than human experts

 E-Mail IMAGE: The graphic shows an image generated by AO-OCT (top), and the result of WeakGCSeg algorithms to identify and trace the shapes of the ganglion cells in the eye (bottom). view more  Credit: Sina Farsiu, Duke University DURHAM, N.C. A new combination of optical coherence tomography (OCT), adaptive optics and deep neural networks should enable better diagnosis and monitoring for neuron-damaging eye and brain diseases like glaucoma. Biomedical engineers at Duke University led a multi-institution consortium to develop the process, which easily and precisely tracks changes in the number and shape of retinal ganglion cells in the eye.

Biomedical engineers at Duke using AI could advance eye disease diagnosis

by Michaela Kane May 6, 2021 . DURHAM – A new combination of optical coherence tomography (OCT), adaptive optics and deep neural networks should enable better diagnosis and monitoring for neuron-damaging eye and brain diseases like glaucoma. Biomedical engineers at Duke University led a multi-institution consortium to develop the process, which easily and precisely tracks changes in the number and shape of retinal ganglion cells in the eye. This work appears in a paper published on May 3 in the journal Optica. The retina of the eye is an extension of the central nervous system. Ganglion cells are one of the primary neurons in the eye that process and send visual information to the brain. In many neurodegenerative diseases like glaucoma, ganglion cells degenerate and disappear, leading to irreversible blindness. Traditionally, researchers use OCT, an imaging technology similar to ultrasound that uses light instead of sound, to peer beneath layers of eye tissue to diagnose and

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