Three-dimensional immersive virtual reality for studying cellular compartments in 3D models from EM preparations of neural tissues
Hamprecht, Fred A.
Magistretti, Pierre J.
KAUST DepartmentBiological and Environmental Sciences and Engineering (BESE) Division
KAUST Visualization Laboratory (KVL)
Permanent link to this recordhttp://hdl.handle.net/10754/561070
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AbstractAdvances for application of electron microscopy to serial imaging are opening doors to new ways of analyzing cellular structure. New and improved algorithms and workflows for manual and semiautomated segmentation allow to observe the spatial arrangement of the smallest cellular features with unprecedented detail in full three-dimensions (3D). From larger samples, higher complexity models can be generated; however, they pose new challenges to data management and analysis. Here, we review some currently available solutions and present our approach in detail. We use the fully immersive virtual reality (VR) environment CAVE (cave automatic virtual environment), a room where we are able to project a cellular reconstruction and visualize in 3D, to step into a world created with Blender, a free, fully customizable 3D modeling software with NeuroMorph plug-ins for visualization and analysis of electron microscopy (EM) preparations of brain tissue. Our workflow allows for full and fast reconstructions of volumes of brain neuropil using ilastik, a software tool for semiautomated segmentation of EM stacks. With this visualization environment, we can walk into the model containing neuronal and astrocytic processes to study the spatial distribution of glycogen granules, a major energy source that is selectively stored in astrocytes. The use of CAVE was key to observe a nonrandom distribution of glycogen, and led us to develop tools to quantitatively analyze glycogen clustering and proximity to other subcellular features. This article is protected by copyright. All rights reserved.
CitationThree-dimensional immersive virtual reality for studying cellular compartments in 3D models from EM preparations of neural tissues 2015:n/a Journal of Comparative Neurology
JournalJournal of Comparative Neurology
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