A picture is worth a thousand words. It’s no wonder why medical imaging is so important, because we can gather so much more information in much less time if we can look at a picture rather than a written description. Imaging technology is an important part of modern healthcare. Camera technology is advancing rapidly, pushed along by larger market developments such as smartphone cameras and digital integrated circuit fabrication. But now comes news of a remarkably small camera technology.
In a paper in Science Advances, researchers from the University of Stuttgart have developed a solid state camera system that is nearly too small to see. It is actually an array of four separate cameras that are fabricated on a microchip. Together, they fit in in a space less than 300 by 300 microns, or about the thickness of three sheets of paper. The system requires four cameras because light waves bend at different angles depending on their wavelength. By combining the images from four cameras and doing some sophisticated processing, the system creates an accurate color image. The design also creates a “foveated” image; there is more detail in the center of the field of view, with less detail towards the outer edges. This is because the four cameras have different focal lengths, so they range from the equivalent of telephoto to wide angle.
The remarkable part is that this entire array is small enough to slip through a syringe needle. This makes it possible to create a minimally-invasive camera system that can be attached to a fiber optic catheter. Physicians can then see inside a patient’s body to inspect specific locations at high resolution — even in the brain — without having to interpret digitized images from X-rays or CAT scans.
The implications for this new technology go far beyond medical applications, however. Imagine inexpensive camera systems the size of a grain of sand. They could be incorporated into all sorts of wearables and other devices, such as ID cards or eyeglass frames. This could lead to all sorts of new solutions ranging from artificial reality (AR) to machine vision.