Mapping the intricate network of nerve fibers is crucial for understanding brain function. Three-Dimensional Polarized Light Imaging (3D-PLI) and Computational Scattered Light Imaging (ComSLI) map dense nerve fibers in brain sections with micrometer resolution using visible light. 3D-PLI reconstructs 3D-fiber orientations, while ComSLI disentangles multiple directions per pixel. So far, these imaging techniques have been realized in separate setups. A combination within a single device would facilitate faster measurements, pixelwise mapping, cross-validation of fiber orientations, and leverage the advantages of each technique while mitigating their limitations. Here, we introduce the Scattering Polarimeter, a microscope that facilitates correlative large-area scans by integrating 3D-PLI and ComSLI measurements into a single system. Based on a Mueller polarimeter, it incorporates variable retarders and a large-area light source for direct and oblique illumination, enabling combined 3D-PLI and ComSLI measurements. Applied to human and vervet monkey brain sections, the Scattering Polarimeter generates results comparable to state-of-the-art 3D-PLI and ComSLI setups and creates a multimodal fiber direction map, integrating the robust fiber orientations obtained from 3D-PLI with fiber crossings from ComSLI. Furthermore, we discuss applications of the Scattering Polarimeter for unprecedented correlative and multimodal brain imaging.

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.

We present a method for direct imaging of nerve fiber orientations in cell-body stained histological brain sections, which was not yet possible for paraffin-treated tissue.