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To study the structure and function of the brain, a detailed reconstruction of the brain’s nerve fiber architecture is required. However, many neuroimaging techniques, such as 3D-Polarized Light Imaging (M. Axer, Amunts, et al., 2011; M. Axer, Grässel, et al., 2011) struggle with the correct reconstruction of crossing nerve fibers. The recently developed technique Scattered Light Imaging (SLI) uses light in the optical range to explore the substructure of (crossing) nerve fibers in whole brain sections with micrometer resolution, providing crucial information such as the orientations of crossing nerve fibers in a measured image pixel (Menzel, Reuter, et al., 2020). The measurement principle was first introduced by Menzel, Axer, et al. (2020). Unstained histological brain sections are illuminated from different angles and the transmitted (scattered) light behind the sample is measured under normal incidence (see Figure 1a). Every pixel in the resulting SLI image series contains a light intensity profile (SLI profile I(φ), cf. Figure 1b-c) which is characteristic for the brain tissue structure at this point. The number and position of significant peaks in the SLI profiles can be used, for example, to determine the individual orientations of (crossing) nerve fibers in each image pixel.

SLIX: A Python package for fully automated evaluation of Scattered Light Imaging measurements on brain tissue