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Technique Interprets Hyperspectral Images Using Phasor Approach

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An imaging technique called spectrally encoded enhanced representations (SEER) provides greater clarity and works up to 67 times faster and at 2.7 times greater definition than existing spectral imaging techniques, according to its developers at the University of Southern California (USC). SEER uses mathematical computations to parse data quickly and achieve simultaneous color visualization of the multiple spectral components of hyperspectral fluorescence images.

SEER transforms wavelength space into color maps for RGB display visualization using the phasor method. Originally developed for fluorescence lifetime analysis, the phasor approach is used by SEER to enhance the visualization of multi- and hyperspectral images.

Spectrally encoded enhanced representations (SEER) technology by USC works up to 67 times faster with 2.7 times greater definition than other techniques. Courtesy of Francesco Cutrale, USC.

Spectrally encoded enhanced representations (SEER) technology by USC works up to 67 times faster with 2.7 times greater definition than other techniques. Courtesy of Francesco Cutrale, USC.

SEER explores the phasor plot as a whole and represents the complete information set as a color image, maintaining efficiency and minimizing user interaction, even with large data sizes. Tests showed that SEER can process a 3.7-GB data set with 1.26 × 108 spectra in 6.6 seconds and a 43.88-GB data set with 1.47 × 109 spectra in 87.3 seconds, including denoising of data.

“There is a number of scenarios where this after-the-fact analysis, while powerful, would be too late in experimental or medical decision-making,” professor Francesco Cutrale said. “There is a gap between acquisition and analysis of the hyperspectral data, where scientists and doctors are unaware of the information contained in the experiment. SEER is designed to fill this gap.”

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The SEER algorithm, first authored by Wen Shi and Daniel Koo at the Translational Imaging Center of USC, will be used for detecting early stages of lung disease and potential damage from pollutants in patients in a collaboration with doctors at Children’s Hospital Los Angeles. The USC researchers said that scientists in the life sciences field have started adopting SEER in their experimental pipelines in an effort to further improve efficiency. In the future, the SEER technology could become a smartphone app for use in remote medicine, food safety, or counterfeit currency detection, Cutrale said.

The research was published in Nature Communications (www.doi.org/10.1038/s41467-020-14486-8). 

Imaging technology, called SEER, developed by USC scientists, produces clearer images faster than existing methods. Courtesy of Francesco Cutrale, USC.

Published: February 2020
Glossary
hyperspectral imaging
Hyperspectral imaging is an advanced imaging technique that captures and processes information from across the electromagnetic spectrum. Unlike traditional imaging systems that record only a few spectral bands (such as red, green, and blue in visible light), hyperspectral imaging collects data in numerous contiguous bands, covering a wide range of wavelengths. This extended spectral coverage enables detailed analysis and characterization of materials based on their spectral signatures. Key...
computational imaging
Computational imaging refers to the use of computational techniques, algorithms, and hardware to enhance or enable imaging capabilities beyond what traditional optical systems can achieve. It involves the integration of digital processing with imaging systems to improve image quality, extract additional information from captured data, or enable novel imaging functionalities. Principles: Computational imaging combines optics, digital signal processing, and algorithms to manipulate and...
Research & TechnologyeducationAmericasUniversity of Southern CaliforniaImagingLight SourcesOpticshyperspectral imagingBiophotonicsmedicalcomputational imagingfluorescence hyperspectral imagingSEERphasor methodMicroscopyBioScan

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