Document Detail


Three-Dimensional Characterization of Iron Oxide (α-Fe2O3) Nanoparticles: Application of a Compressed Sensing Inspired Reconstruction Algorithm to Electron Tomography.
MedLine Citation:
PMID:  23211355     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
In this article, we demonstrate the application of a new compressed sensing three-dimensional reconstruction algorithm for electron tomography that increases the accuracy of morphological characterization of nanostructured materials such as nanocrystalline iron oxide particles. A powerful feature of the algorithm is an anisotropic total variation norm for the L1 minimization during algebraic reconstruction that effectively reduces the elongation artifacts caused by limited angle sampling during electron tomography. The algorithm provides faithful morphologies that have not been feasible with existing techniques.
Authors:
Niven Monsegue; Xin Jin; Takuya Echigo; Ge Wang; Mitsuhiro Murayama
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-12-5
Journal Detail:
Title:  Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada     Volume:  -     ISSN:  1435-8115     ISO Abbreviation:  Microsc. Microanal.     Publication Date:  2012 Dec 
Date Detail:
Created Date:  2012-12-5     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9712707     Medline TA:  Microsc Microanal     Country:  -    
Other Details:
Languages:  ENG     Pagination:  1-6     Citation Subset:  -    
Affiliation:
Institute for Critical Technology and Applied Science, Virginia Tech, Blacksburg, VA 24061, USA.
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