Estimating fiber orientation distribution functions in 3D-Polarized Light Imaging

Research of the human brain connectome requires multiscale approaches derived from independent imaging methods ideally applied to the same object. Hence, comprehensible strategies for data integration across modalities and across scales are essential. We have successfully established a concept to br...

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Bibliographic Details
Published in:Frontiers in Neuroanatomy
Main Authors: Markus eAxer, Sven eStrohmer, David eGräßel, Oliver eBücker, Melanie eDohmen, Julia eReckfort, Karl eZilles, Katrin eAmunts
Format: Article in Journal/Newspaper
Language:English
Published: Frontiers Media S.A. 2016
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Online Access:https://doi.org/10.3389/fnana.2016.00040
https://doaj.org/article/9706edb4ca6c48e1837a390b8f565b7f
Description
Summary:Research of the human brain connectome requires multiscale approaches derived from independent imaging methods ideally applied to the same object. Hence, comprehensible strategies for data integration across modalities and across scales are essential. We have successfully established a concept to bridge the spatial scales from microscopic fiber orientation measurements based on 3D-Polarized Light Imaging (3D-PLI) to meso- or macroscopic dimensions. By creating orientation distribution functions (pliODFs) from high-resolution vector data via series expansion with spherical harmonics utilizing high performance computing and supercomputing technologies, data fusion with Diffusion Magnetic Resonance Imaging has become feasible, even for a large-scale dataset such as the human brain. Validation of our approach was done effectively by means of two types of datasets that were transferred from fiber orientation maps into pliODFs: simulated 3D-PLI data showing artificial, but clearly defined fiber patterns and real 3D-PLI data derived from sections through the human brain and the brain of a hooded seal.