A Stare-Down Video-Rate High-Throughput Hyperspectral Imaging System and Its Applications in Biological Sample Sensing

Abstract

Hyperspectral imaging (HSI) combines spectroscopy and 2-D imaging to reveal sample composition and properties. Video level HSI helps to observe and analyze molecular features in dynamic processes. However, maintaining a high imaging speed will sacrifice spectral and spatial resolution. For real-time dynamic biological samples monitoring with high spectral and spatial resolution, this work proposes a novel HSI system, which includes a high-speed galvo mirror and a 10-Gb ethernet port CMOS sensor for spatial scanning and data acquisition. The galvo mirror can scan spatial light, accelerating the collection rate of hyperspectral cubes to the video level. The CMOS sensor can directly collect spectral spatial optical data at a speed of 1600 frames/s and synchronously outputs the data. Theoretically, this system can achieve <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${N}$ </tex-math></inline-formula> cubes/s with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$624\times $ </tex-math></inline-formula> (1600/ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${N}$ </tex-math></inline-formula> ) <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times500$ </tex-math></inline-formula> resolutions, whose spectral bands and resolution are 500 and 3–5 nm, respectively. This is the first time hyperspectral data have been obtained at such a high throughput and cube rate. Chlorophyll sensing and mouse tumor localization were carried out to verify the system effectiveness. Hyperspectral videos of human palms both under stress and in a relaxed state, and hyperspectral videos of jellyfish navigation through water are recorded, considering the signal-to-noise ratio, the acquisition speed is reduced to one cube per second, and the acquisition cube size is expanded to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$624\times 1600\times500$ </tex-math></inline-formula> . Then, spectral data are extracted from keyframes of the video to observe changes in molecular information. This promising tool offers great potential for living being detection.