Eye doctors could be using computing power to help them see individual retinal cells. Researchers hope that the detailed pictures gleaned from applying computational adaptive optics can illuminate how changes in the retina correspond to disease severity and track how cells and nerves respond to treatments. Detailed pictures of the cells, blood vessels and nerves at the back of the eye could enable earlier diagnosis and better treatment for degenerative eye and neurological diseases.
Hardware-based adaptive optics systems have been developed by Prof. Stephen Allen Boppart's research team. to enhance optical coherence tomography (OCT) imaging with elaborate setups of lenses, mirrors, and lasers. The technique applies adaptive optics – the method astronomers use to correct telescope images so they can more clearly see stars beyond the twinkling – to the instruments that scan the retina at the back of the eye.
However, the Illinois team does the correction computationally, instead of using complex hardware. The research team published its work in the journal Nature Photonics.
The prevailing imaging technique in ophthalmology is the OCT, which is useful for general imaging of the eye but cannot focus down to the scale of individual rods and cones, the light-sensitive cells lining the retina that make sight possible. In addition, OCT images are often blurred by the eye’s imperfections and constant motion.
Computational adaptive optics applies complex algorithms to OCT data correcting for eye aberrations and motion, yielding high-resolution, real-time images that show individual cells and nerves.
Hardware-based adaptive optics systems have been developed to enhance OCT imaging with elaborate setups of lenses, mirrors and lasers, but such systems are so costly and unwieldy that they are impractical for clinical use. However, the new computational approach could be applied to existing OCT systems, with minor hardware updates to older systems for compatibility.
Computational adaptive optics also hold an advantage over hardware setups in that they can tailor themselves to a patient’s unique eye structures and shape, and doctors can take one quick scan and afterward focus in on different parts of the eye.
The researchers are initially focusing on using computational adaptive optics to track age-related macular degeneration, a progressive eye disease, and multiple sclerosis, a progressive neurological disease.
Because nerve fibers make up the top layer of the retina, the eye could be a unique window into nerve health for multiple sclerosis patients. The researchers hope that the detailed pictures gleaned from applying computational adaptive optics can illuminate how changes in the retina correspond to disease severity and track how cells and nerves respond to treatments.
The National Institutes of Health and the National Science Foundation supported this work. Dr Boppart also is affiliated with the Beckman Institute for Advanced Science and Technology and the departments of bioengineering and internal medicine at the U. of I.
From U of I News Bureau
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However, the Illinois team does the correction computationally, instead of using complex hardware. The research team published its work in the journal Nature Photonics.
The prevailing imaging technique in ophthalmology is the OCT, which is useful for general imaging of the eye but cannot focus down to the scale of individual rods and cones, the light-sensitive cells lining the retina that make sight possible. In addition, OCT images are often blurred by the eye’s imperfections and constant motion.
Computational adaptive optics applies complex algorithms to OCT data correcting for eye aberrations and motion, yielding high-resolution, real-time images that show individual cells and nerves.
Hardware-based adaptive optics systems have been developed to enhance OCT imaging with elaborate setups of lenses, mirrors and lasers, but such systems are so costly and unwieldy that they are impractical for clinical use. However, the new computational approach could be applied to existing OCT systems, with minor hardware updates to older systems for compatibility.
Computational adaptive optics also hold an advantage over hardware setups in that they can tailor themselves to a patient’s unique eye structures and shape, and doctors can take one quick scan and afterward focus in on different parts of the eye.
Because nerve fibers make up the top layer of the retina, the eye could be a unique window into nerve health for multiple sclerosis patients. The researchers hope that the detailed pictures gleaned from applying computational adaptive optics can illuminate how changes in the retina correspond to disease severity and track how cells and nerves respond to treatments.
The National Institutes of Health and the National Science Foundation supported this work. Dr Boppart also is affiliated with the Beckman Institute for Advanced Science and Technology and the departments of bioengineering and internal medicine at the U. of I.
From U of I News Bureau
Read about Retina Global here.
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