Towards high-speed computational scattered light imaging by introducing compressed sensing for optimized illumination

Franca Auf Der Heiden*, Oliver Münzer, Simon Van Staalduine, Katrin Amunts, Markus Axer, Miriam Menzel

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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Abstract

We propose the application of Compressed Sensing to Computational Scattered Light Imaging to decrease measurement time and data storage. Computational Scattered Light Imaging (ComSLI) determines three-dimensional fiber orientations and crossings in biomedical tissues like brain tissue. Currently, conventional ComSLI is time-consuming and generates large data. Compressed Sensing reconstructs signals with fewer samples than required by the Shannon-Nyquist theorem with minimal perceptual loss, significantly reducing the number of measurements. We introduce an optimized illumination strategy for ComSLI based on the Discrete Cosine Transform and validate it by reconstructing characteristic scattering patterns in vervet brain tissue, thereby demonstrating the feasibility of Compressed Sensing in ComSLI.

Original languageEnglish
Title of host publicationHigh-Speed Biomedical Imaging and Spectroscopy IX
EditorsKevin K. Tsia, Keisuke Goda
PublisherSPIE
ISBN (Electronic)9781510669659
DOIs
Publication statusPublished - 2024
EventHigh-Speed Biomedical Imaging and Spectroscopy IX 2024 - San Francisco, United States
Duration: 27 Jan 202428 Jan 2024

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume12853
ISSN (Print)1605-7422

Conference

ConferenceHigh-Speed Biomedical Imaging and Spectroscopy IX 2024
Country/TerritoryUnited States
CitySan Francisco
Period27/01/2428/01/24

Keywords

  • Brain Structure
  • Compressed Sensing
  • Discrete Cosine Transform
  • Nerve Fibers
  • Neuroimaging
  • Scattered Light Imaging
  • Scatterometry
  • White Matter

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