Login / Signup

Fourier transforms for fast and quantitative Laser Speckle Imaging.

Jesse BuijsJ van der GuchtJoris Sprakel
Published in: Scientific reports (2019)
Laser speckle imaging is a powerful imaging technique that visualizes microscopic motion within turbid materials. At current two methods are widely used to analyze speckle data: one is fast but qualitative, the other quantitative but computationally expensive. We have developed a new processing algorithm based on the fast Fourier transform, which converts raw speckle patterns into maps of microscopic motion and is both fast and quantitative, providing a dynamnic spectrum of the material over a frequency range spanning several decades. In this article we show how to apply this algorithm and how to measure a diffusion coefficient with it. We show that this method is quantitative and several orders of magnitude faster than the existing quantitative method. Finally we harness the potential of this new approach by constructing a portable laser speckle imaging setup that performs quantitative data processing in real-time on a tablet.
Keyphrases
  • high resolution
  • high speed
  • machine learning
  • deep learning
  • magnetic resonance imaging
  • systematic review
  • electronic health record
  • magnetic resonance
  • big data
  • fluorescence imaging
  • data analysis