A technique developed to computationally correct for aberrations is helping to produce higher-quality images and 3D datasets for real-time imaging applications such as image-guided surgery, cancer diagnosis, and ophthalmology. Called computational adaptive optics, it can be applied to any type of interferometric imaging, such as optical coherence tomography (OCT). And because the computations can be performed on an ordinary desktop computer, the approach is accessible for many hospitals and clinics.1
Adaptive optics typically involves the use of mirrors to smooth out scattered light before it enters a lens. The new approach uses computer software to find and correct aberrations after the image is taken. Once a tissue sample is scanned using an interferometric microscope (which uses two beams of light), the computer collects all of the data and then corrects the images at all depths within the volume. Researchers at the University of Illinois (U of I; Champaign, IL) led by Stephen Boppart, professor of electrical and computer engineering, bioengineering, and internal medicine, teamed up with Scott Carney, professor of electrical and computer engineering and the head of the Optical Science Group at the Beckman Institute, to develop the computational adaptive optics approach. Boppart's group previously developed various handheld devices for imaging the eye. "Because of the aberrations of the human eye, when you look at the retina without adaptive optics you just see variations of light and dark areas that represent the rods and cones. But when you use adaptive optics, you see the rods and cones as distinct objects," he explains. Adaptive optics hardware is too expensive or too complicated for most practicing ophthalmologists, the researchers say, but a computational solution could allow more ophthalmologists to examine and treat their patients effectively.
Because the approach corrects data post-acquisition, the researchers have been able to develop microscope systems that maximize light collection instead of worrying about minimizing aberrations-an effort that could produce better data for better image rendering. The researchers are now working to refine the algorithms and explore applications, including real-time in-vivo applications for surgery, minimally invasive biopsy, and others.
1. S. G. Adie et al., PNAS, 1121193109v1-7180 (2012).