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.
Three-dimensional Polarized Light Imaging (3D-PLI) enables the investigation of nerve fibers in the brain by probing their birefringence with polarimetric measurements of unstained brain sections. Based on a biophysical model, it allows the estimation of the three-dimensional fiber orientation. In this work, a novel probabilistic approach capable of providing confidence measures for the inferred fiber orientation is introduced. The developed analysis utilizes Bayesian inference to derive a distribution for the model parameters. Simulations show that the obtained confidence measures are accurate. On human brain data, the novel algorithm enables to quantify levels of confidence in 3D-PLI for the first time. The method shows that fiber orientation estimation in 3D-PLI is robust for white matter regions.
In this work, we employ an integrated label-free dual approach that combines Polarized
Light Imaging with Two-Photon Fluorescence Microscopy to study fiber orientations of
myelinated axons in fixed brain slices from different species.
3D-Polarized Light Imaging (3D-PLI) is a unique technique that enables high-resolution three-dimensional mapping
of the nerve fiber architecture in unstained histological sections of the human brain. 3D-PLI is based on
the detection of the intrinsic tissue birefringence caused by the nerve fibers. The measured birefringent signals
comprise entangled information on both spatial fiber orientation and the local fiber density.
In this study, we introduce a novel approach to effectively and unambiguously unravel this interrelation, for
providing a reliable estimation of fiber orientations in the entire human brain. The method relies on an in-house
developed polarimetric device equipped with a tiltable specimen stage. Each brain section is measured from
different perspectives and the obtained data sets are processed with a dedicated Fourier analysis optimized for
fast computation and shot noise stability.
For the first time it is demonstrated, that the prevailing orientations of cortical fibers can be quantified in the
three-dimensional space and traced back into the white matter. Moreover, the approach provides descriptions of variances in fiber density. Hence, the method presented here opens new perspectives for the neuroanatomical
study of the human cortex.
The neuroimaging technique 3D-polarized light imaging (3D-PLI) has opened up new avenues to study the complex nerve fiber architecture of the human brain at sub-millimeter spatial resolution. This polarimetry technique is applicable to histological sections of postmortem brains utilizing the birefringence of nerve fibers caused by the regular arrangement of lipids and proteins in the myelin sheaths surrounding axons. 3D-PLI provides a three-dimensional description of the anatomical wiring scheme defined by the in-section direction angle and the out-of-section inclination angle. To date, 3D-PLI is the only available method that allows bridging the microscopic and the macroscopic description of the fiber architecture of the human brain. Here we introduce a new approach to retrieve the inclination angle of the fibers independently of the properties of the used polarimeters. This is relevant because the image resolution and the signal transmission inuence the measured birefringent signal (retardation) significantly. The image resolution was determined using the USAF- 1951 testchart applying the Rayleigh criterion. The signal transmission was measured by elliptical polarizers applying the Michelson contrast and histological slices of the optic tract of a postmortem brain. Based on these results, a modified retardation-inclination transfer function was proposed to extract the fiber inclination. The comparison of the actual and the inclination angles calculated with the theoretically proposed and the modified transfer function revealed a significant improvement in the extraction of the fiber inclinations.
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