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            Chapter 3D Polarized Light Imaging Portrayed: Visualization of Fiber Architecture Derived from 3D-PLI

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            Author(s)
            Schubert, Nicole
            Axer, Markus
            Pietrzyk, Uwe
            Amunts, Katrin
            Language
            English
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            Abstract
            3D polarized light imaging (3D-PLI) is a neuroimaging technique that has recently opened up new avenues to study the complex architecture of nerve fibers in postmortem brains at microscopic scales. In a specific voxel-based analysis, each voxel is assigned a single 3D fiber orientation vector. This leads to comprehensive 3D vector fields. In order to inspect and analyze such high-resolution fiber orientation vector field, also in combination with complementary microscopy measurements, appropriate visualization techniques are essential to overcome several challenges, such as the massive data sizes, the large amount of both unique and redundant information at different scales, or the occlusion issues of inner structures by outer layers. Here, we introduce a comprehensive software tool that is able to visualize all information of a typical 3D-PLI dataset in an adequate and sophisticated manner. This includes the visualization of (i) anatomic structural and fiber architectonic data in one representation, (ii) a large-scale fiber orientation vector field, and (iii) a clustered version of the field. Alignment of a 3D-PLI dataset to an appropriate brain atlas provides expert-based delineation, segmentation, and, ultimately, visualization of selected anatomical structures. By means of these techniques, a detailed analysis of the complex fiber architecture in 3D is feasible.
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/151767
            Keywords
            polarized light imaging, scientific visualization, neuroinformatics, neuroimaging and fiber architecture; thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences
            DOI
            10.5772/intechopen.72532
            Publisher
            InTechOpen
            Publication date and place
            2018
            Grantor
            • H2020 Science with and for Society
            • OAPEN harvesting collection

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            • logo EUEuropean Union
              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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