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JUL/AUG 2013  

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A high-resolution endoscope as thin as a human hair

Engineers at Stanford have developed a prototype single-fiber endoscope that is as thin as a human hair with a resolution four times better than previous devices of similar design, according to Stanford University. The advance could lead to an era of needle-thin, minimally invasive endoscopes able to view features out of reach of today’s instruments, the university reports.

The micro-endoscope is a significant step forward in high-resolution, minimally invasive bio-imaging with potential applications in research and clinical practice, according to the researchers at the university. Micro-endoscopy could enable new methods in diverse fields ranging from study of the brain to early cancer detection.

The new endoscope was developed by a team under the direction of Joseph Kahn, professor of electrical engineering at the Stanford School of Engineering. The results were published recently in the journal Optics Express and showcased in the Optical Society of America’s Spotlight on Optics.

The prototype can resolve objects as small as 2.5µm with a resolution of about 0.3µm. A micron is one thousandth of a millimeter. By comparison, today’s high-resolution endoscopes can resolve objects only to about 10µm. The naked eye can see objects down to about 125µm.

In Kahn’s micro-endoscope, the spatial light modulator projects random light patterns through the fiber into the body to illuminate the object under observation. The light reflecting off the object returns through the fiber to a computer. The computer, in turn, measures the reflected power of the light and uses algorithms developed by Nasiri Mahalati and fellow graduate student Ruo Yu Gu to reconstruct an image.

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kahn schematic

A schematic rendering of Professor Joseph Kahn's rigid endoscope using a multimode optical fiber. Random patterns of light generated by a spatial light modulator pass through a fiber and illuminate a region near the fiber tip. Reflected power values are recorded and used to reconstruct an image. The arrows indicate the direction of light travel. Illustration credit: Joseph Kahn, Stanford School of Engineering