Technological advancements have provided a strong base to biotechnology and recording even the most sensitive transformations in biology. In this aspect, an essential step in the treatment of the disease is to first understand how the disease works. To do this, scientists need to look carefully at the source of the disease. Deep imaging of living organisms such as cells, fish and humans has always been a bottleneck for biologists, yet with the invention of fluorescent tags, Raman microscopy and numerous nondestructive imaging techniques. When it comes to get an inside picture of the organism, biologists follow the technique called Fluorescent ultra-spectroscopic imaging (fHSI). This method can differentiate colors across the spectrum and tag molecules to produce vivid color images inside the organism. Data collection is, however, a problem. Because fHSI generates a large amount of data due to the complexity of the biological system, the data is analyzed after collection, leaving gaps in the process timeline without any information. In certain scenarios, “late” data can kill research or medical outcomes.
To fill this gap, researchers at the University of Southern California developed a novel algorithm called spectrally encoded enhanced representations (SEER) that is focused on enhancing the visualization of hyperspectral data. The algorithm performs up to 67 times faster and at 2.7-fold higher accuracy than present techniques. The key to SEER stands in its ability to uncover the subtle changes, which are often the crucial most clues within the biological systems. Current methods focus on interpreting data the same way our eyes would perceive it, while SEER can process vibrant fluorescent tags across the full spectrum of colors, discriminating very subtle color and spectral differences between samples.
“SEER exploits our previously developed denoising algorithms and combines them with a novel set of adaptive ‘Fourier space’ color maps to enhance the visualization of small color differences,” lead author and USC professor Francesco Cutrale explained to Laboratory Equipment. “This pre-processing step is meant as a rapid interface for any user with the content of information of hyperspectral technology.” Cutrale further added, “Our study showed rapid visualization of differences in metabolism in cells of the airway, corresponding to different roles of cells. The metabolic readout can be informative of the overall health of the tissue, for example, when affected by external factors such as pollution or disease”.
