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Innovative Imaging to Study Causes of Glaucoma

The University of Maryland, Baltimore (UMB) is the state’s public health, law, and human services university devoted to excellence in professional and graduate education, research, patient care, and public service.

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.

New technology makes it easier to diagnose neurodegenerative diseases

New technology makes it easier to diagnose neurodegenerative diseases 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

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

Macrophages of the Human Eye Come into Focus

The paper PNAS, 117:30661–69, 2020. Staring at her images of neurons in living humans’ eyes, Zhuolin Liu got an inkling that she could also see traces of another cell type on the surface of the retina. The images came from a study completed as part of her postdoctoral research at Indiana University (IU) Bloomington, and though the focus of that work had been neurons in the retina, the glimpse she got of what looked like macrophages led her to wonder if she and her colleagues could get a better view of the immune cells and probe their dynamics.   Macrophages on the surface of the retina look and act like microglia, the sentinels of the central nervous system. They had been studied extensively in rodents but haven’t been visualized in real time in the eyes of living humans. Doing so, says her collaborator Daniel Hammer, a researcher at the US Food and Drug Administration (FDA), would offer a better understanding of how they protect the eye. “People are familiar with the [sa

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