New ultra-miniaturized microendoscope produces higher-quality images at a fraction of the size

The lensless scope is the width of a few strands of hair and able to capture images of live neuron activity

Johns Hopkins engineers have created a new lens-free, ultra-miniaturized endoscope—the width of only a few human hairs—that is capable of producing high-quality images.

Their findings were published today in Science Advances.

"Usually, you have to sacrifice either size or image quality. We've been able to achieve both with our microendoscope," says Mark Foster, an associate professor of electrical and computer engineering at Johns Hopkins University and the study's corresponding author.

Microendoscopes are designed to examine neurons as they fire in the brains of animal test subjects, and accordingly must be minuscule in scale yet powerful enough to produce a clear image. Most standard microendoscopes are about half a millimeter to a few millimeters in diameter and require larger, more invasive lenses to achieve high-quality imaging. While lensless microendoscopes exist, the optical fiber that scans an area of the brain pixel by pixel frequently bends and loses imaging ability when moved.

In their new study, Foster and colleagues created a lens-free, ultra-miniaturized microendoscope that, compared to a conventional lens-based microendoscope, increases the amount researchers can see and improves image quality. To test their device, they examined beads in different patterns on a slide.

Composite shows 12 images captured by microscopes and microendoscopes to compare clarity

Image caption: The image above shows imaging results from the study. Images A through C show images viewed through a bulk microscope. D through F show the images as viewed through a conventional, lens-based microendoscope. G through I show the images as seen by the new lensless microendoscope. These raw images are purposefully scattered, but provide important information about light that can be used in computational reconstruction to create clearer images, shown in J through L.

Image credit: Courtesy of Mark Foster

The researchers achieved this by using a coded aperture—a flat grid that randomly blocks light, creating a projection in a known pattern, akin to randomly poking a piece of aluminum foil and letting light through all of the small holes. This creates a messy image, but one that provides a bounty of information about where the light originates, and that information can be computationally reconstructed into a clearer image.

"For thousands of years, the goal has been to make an image as clear as possible," Foster says. "Now, thanks to computational reconstruction, we can purposefully capture something that looks awful and counterintuitively end up with a clearer final image."

Additionally, Foster's team's microendoscope doesn't require movement to focus on objects at different depths; they use computational refocusing to determine where the light originated from in three dimensions. This allows their endoscope to be much smaller than traditional versions.

Looking forward, the research team will test their microendoscope with fluorescent labeling procedures, in which active brain neurons are tagged and illuminated, to determine the endoscope's accuracy in imaging neural activity.