000216375 001__ 216375
000216375 005__ 20181228151110.0
000216375 0247_ $$2doi$$a10.1002/cne.23852
000216375 022__ $$a0021-9967
000216375 02470 $$2ISI$$a000365719500003
000216375 037__ $$aARTICLE
000216375 245__ $$aThree-dimensional immersive virtual reality for studying cellular compartments in 3D models from EM preparations of neural tissues
000216375 260__ $$bWiley-Blackwell$$c2016$$aHoboken
000216375 269__ $$a2016
000216375 300__ $$a16
000216375 336__ $$aJournal Articles
000216375 520__ $$aAdvances in the application of electron microscopy (EM) 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 us to observe the spatial arrangement of the smallest cellular features with unprecedented detail in full three-dimensions. 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 in which 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 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 the observation of a nonrandom distribution of glycogen, and led us to develop tools to quantitatively analyze glycogen clustering and proximity to other subcellular features. (c) 2015 Wiley Periodicals, Inc.
000216375 6531_ $$aglycogen clustering
000216375 6531_ $$aglycogen spatial distribution
000216375 6531_ $$a3D navigation
000216375 6531_ $$a3D analysis
000216375 6531_ $$avolume analysis
000216375 6531_ $$afast 3D reconstruction
000216375 700__ $$uKAUST, Biol & Environm Sci & Engn Div, Thuwal 239556900, Saudi Arabia$$aCali, Corrado
000216375 700__ $$uKAUST, Biol & Environm Sci & Engn Div, Thuwal 239556900, Saudi Arabia$$aBaghabra, Jumana
000216375 700__ $$uKAUST, Biol & Environm Sci & Engn Div, Thuwal 239556900, Saudi Arabia$$aBoges, Daniya J.
000216375 700__ $$uKAUST, Biol & Environm Sci & Engn Div, Thuwal 239556900, Saudi Arabia$$aHolst, Glendon R.
000216375 700__ $$uHeidelberg Univ, Heidelberg Collaboratory Image Proc HCI, D-69115 Heidelberg, Germany$$aKreshuk, Anna
000216375 700__ $$uHeidelberg Univ, Heidelberg Collaboratory Image Proc HCI, D-69115 Heidelberg, Germany$$aHamprecht, Fred A.
000216375 700__ $$uKing Abdullah Univ Sci & Technol, KVL, Thuwal 239556900, Saudi Arabia$$aSrinivasan, Madhusudhanan
000216375 700__ $$uKAUST, Biol & Environm Sci & Engn Div, Thuwal 239556900, Saudi Arabia$$aLehvaeslaiho, Heikki
000216375 700__ $$g134990$$uKAUST, Biol & Environm Sci & Engn Div, Thuwal 239556900, Saudi Arabia$$aMagistretti, Pierre J.$$0243698
000216375 773__ $$j524$$tJournal Of Comparative Neurology$$k1$$q23-38
000216375 909C0 $$xU11150$$0252265$$pLNDC
000216375 909CO $$qSV$$particle$$ooai:infoscience.tind.io:216375
000216375 917Z8 $$x219572
000216375 937__ $$aEPFL-ARTICLE-216375
000216375 973__ $$rREVIEWED$$sPUBLISHED$$aEPFL
000216375 980__ $$aARTICLE