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

Conference paper (2024)

Authors

F.K. auf der Heiden Forschungszentrum Jülich
Oliver Münzer Forschungszentrum Jülich
Katrin Amunts Forschungszentrum Jülich
Markus Axer Forschungszentrum Jülich
Miriam Menzel ImPhys/Menzel group - AS , Forschungszentrum Jülich
Research Group
ImPhys/Menzel group (AS) (TU Delft)
Scatterometry Discrete Cosine Transform Compressed Sensing Neuroimaging Scattered Light Imaging Brain Structure Nerve Fibers White Matter
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Published Date

2024

Language

English

Reuse Rights

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Faculty

Applied Sciences

Department

ImPhys/Imaging Physics

Research Group

ImPhys/Menzel group

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.

Files

1285303.pdf
(.pdf | 4.48 Mb)