Fluorescence lifetime imaging (FLI) is a common laboratory technique used in the life sciences for analyzing samples based on how long fluorescent light is generated after the sample is illuminated. Because the time frames involved are extremely short, the illumination has to be very quick and the detectors quite sensitive. This means expensive equipment, careful calibration, and results that are only within frequency- or time-domain modalities.
MIT researchers have developed a new fluorescence lifetime imaging technique that relies on a Microsoft Kinect 3D camera that, while too slow for traditional FLI, is used in a novel way to extract FLI data.
Here’s how an MIT report describes the technology:
The Media Lab researchers represent the optical signal returning from the sample as the sum of 50 different frequencies. Some of those frequencies are higher than that of the signal itself, which is how they are able to recover information about fluorescence lifetimes shorter than the duration of the emitted burst of light.
For each of those 50 frequencies, the researchers measure the difference in phase between the emitted signal and the returning signal. If an electromagnetic wave can be thought of as a regular up-and-down squiggle, phase is the degree of alignment between the troughs and crests of one wave and those of another. In fluorescence imaging, phase shift also carries information about the fluorescence lifetime.
Not all of the light that strikes the biological sample is absorbed; some of it is reflected back. The MIT researchers’ system takes the measurements of incoming light and fits them to a mathematical model of the overlapping intensity profiles of both reflected and re-emitted light.
Once it’s deduced the intensity profile of the reflected light, it can calculate the distance between the emitter and the sample. So unlike conventional fluorescence lifetime imaging, the researchers’ approach doesn’t require distance calibration.
Study in Optica: Blind and reference-free fluorescence lifetime estimation via consumer time-of-flight sensors…
Source: MIT…