@inproceedings{851bf03f0bbb47e2acb19927b22b2775,
title = "Towards high-speed computational scattered light imaging by introducing compressed sensing for optimized illumination",
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.",
keywords = "Brain Structure, Compressed Sensing, Discrete Cosine Transform, Nerve Fibers, Neuroimaging, Scattered Light Imaging, Scatterometry, White Matter",
author = "{Auf Der Heiden}, Franca and Oliver M{\"u}nzer and {Van Staalduine}, Simon and Katrin Amunts and Markus Axer and Miriam Menzel",
year = "2024",
doi = "10.1117/12.3000869",
language = "English",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Tsia, {Kevin K.} and Keisuke Goda",
booktitle = "High-Speed Biomedical Imaging and Spectroscopy IX",
address = "United States",
note = "High-Speed Biomedical Imaging and Spectroscopy IX 2024 ; Conference date: 27-01-2024 Through 28-01-2024",
}