Conexiant
Login
  • The Analytical Scientist
  • The Cannabis Scientist
  • The Medicine Maker
  • The Ophthalmologist
  • The Pathologist
  • The Traditional Scientist
The Analytical Scientist
  • Explore

    Explore

    • Latest
    • News & Research
    • Trends & Challenges
    • Keynote Interviews
    • Opinion & Personal Narratives
    • Product Profiles
    • App Notes

    Featured Topics

    • Mass Spectrometry
    • Chromatography
    • Spectroscopy

    Issues

    • Latest Issue
    • Archive
  • Topics

    Techniques & Tools

    • Mass Spectrometry
    • Chromatography
    • Spectroscopy
    • Microscopy
    • Sensors
    • Data & AI

    • View All Topics

    Applications & Fields

    • Clinical
    • Environmental
    • Food, Beverage & Agriculture
    • Pharma & Biopharma
    • Omics
    • Forensics
  • People & Profiles

    People & Profiles

    • Power List
    • Voices in the Community
    • Sitting Down With
    • Authors & Contributors
  • Business & Education

    Business & Education

    • Innovation
    • Business & Entrepreneurship
    • Career Pathways
  • Events
    • Live Events
    • Webinars
  • Multimedia
    • Video
Subscribe
Subscribe

False

The Analytical Scientist / Issues / 2019 / May / Now Streaming: Spectral Simplification
Spectroscopy Clinical

Now Streaming: Spectral Simplification

A preference algorithm originally developed for Netflix could speed up Raman imaging, readying the tool for potential clinical use

By Jonathan James 05/10/2019 1 min read

Share

Raman imaging has already shown promise as a diagnostic tool, both to identify cancer cells in tissue samples and to detect disease biomarkers. But slow imaging and the production of unwieldy amounts of data have thus far hampered its use in clinical settings, where speed and efficiency are essential. In an effort to solve the problem, a team of researchers at École Normale Supérieure in Paris has turned to a most unlikely source: Netflix.

Repurposing an algorithm originally developed in 2009 as part of a competition to develop more accurate movie preference software for the streaming giant (1), the group hoped to make use of the substantial predictive power to “fill in the gaps” in spectroscopic images. By predicting the make-up of unimaged sections of samples, the analysis time and volume of spectral data necessary to determine a samples chemical composition can be reduced.

“We combined compressive imaging with fast computer algorithms that provide the kind of images clinicians use to diagnose patients, but rapidly and without laborious manual postprocessing,” said team leader Hilton de Aguiar (2).

The team also tackled cost by replacing the camera normally associated with Raman imaging with a spatial light modulator. “The device we used is orders of magnitude less expensive and faster than other options on the market,” says Aguiar. To test the camera’s ability to distinguish high levels of chemical complexity, the team prepared samples of brain tissue and single cells, and were rewarded with their newfound ability to acquire spectral data – compressed by 64 times – in tens of seconds as opposed to the minutes or hours taken by other approaches (3).

If further testing on other biological samples proves successful, clinicians may one day gain access to a rapid new diagnostic tool, which – much to the relief of patients everywhere – will presumably not require a monthly subscription.

The researchers demonstrated their new methodology by using a Raman microscope to obtain spectroscopy images from opaque brain tissue. Scale bar: 20 microns. Credit: Hilton De Aguiar, École Normale Supérieure

Newsletters

Receive the latest analytical science news, personalities, education, and career development – weekly to your inbox.

Newsletter Signup Image

References

  1. Netflix, “Netflix Prize,” (2009) Available at: https://bit.ly/2DBQE7l Accessed April 8, 2019. The Optical Society, “Researchers Use Algorithm from Netflix Challenge to Speed up Biological Imaging” (2019). Available at: https://bit.ly/2WhB5tS. Accessed May 3, 2019. F Soldevila et al., “Fast compressive Raman bio-imaging via matrix completion”, Optica, 6, 341–6 (2019). DOI: 10.1364/ OPTICA.6.000341.

About the Author(s)

Jonathan James

Having thrown myself into various science communication activities whilst studying science at University, I soon came to realize where my passions truly lie; outside the laboratory, telling the stories of the remarkable men and women conducting groundbreaking research. Now, at Texere, I have the opportunity to do just that.

More Articles by Jonathan James

False

Advertisement

Recommended

False

False

The Analytical Scientist
Subscribe

About

  • About Us
  • Work at Conexiant Europe
  • Terms and Conditions
  • Privacy Policy
  • Advertise With Us
  • Contact Us

Copyright © 2025 Texere Publishing Limited (trading as Conexiant), with registered number 08113419 whose registered office is at Booths No. 1, Booths Park, Chelford Road, Knutsford, England, WA16 8GS.