Adaptive optics imaging method shows individual cells in the eye

A computational adaptive optics technique could help ophthalmologists see individual cells in the back of a patient's eye.

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Engineers at the University of Illinois have developed a computational adaptive optics technique that could help ophthalmologists see individual cells in the back of a patient's eye. Such 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.

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Adaptive optics is used by astronomers to correct telescope images so they can more clearly see stars beyond the twinkling, and can be used with instruments that scan the retina at the back of the eye. However, the Illinois research team—led by electrical and computer engineering professor Stephen Boppart—does the correction computationally instead of using complex hardware.

The prevailing imaging technique in ophthalmology, known as optical coherence tomography (OCT), 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. So the researchers used computational adaptive optics to apply complex algorithms to OCT data to correct for eye aberrations and motion, yielding high-resolution, real-time images that show individual cells and nerves.

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New technology uses computational techniques to more clearly see individual rods and cones, the cells that detect light in the back of the eye. (Graphic by Alex Jerez Roman)

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, Boppart says. 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. Since nerve fibers make up the top layer of the retina, the eye could be a unique window into nerve health for multiple sclerosis patients, Boppart says. 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.

Full details of the work appear in the journal Nature Photonics; for more information, please visit

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