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Detalle de: Three-Dimensional Chemical Mapping by EFTEM-TomoJ Including Improvement of SNR by PCA and ART Reconstruction of Volume by Noise Suppression

Title Three-Dimensional Chemical Mapping by EFTEM-TomoJ Including Improvement of SNR by PCA and ART Reconstruction of Volume by Noise Suppression
Abstract

Electron tomography is becoming one of the most used methods for structural analysis at nanometric scale in biological and materials sciences. Combined with chemical mapping, it provides qualitative and semiquantitative information on the distribution of chemical elements on a given sample. Due to the current difficulties in obtaining three-dimensional (3D) maps by energy-filtered transmission electron microscopy (EFTEM), the use of 3D chemical mapping has not been widely adopted by the electron microscopy community. The lack of specialized software further complicates the issue, especially in the case of data with a low signal-to-noise ratio (SNR). Moreover, data interpretation is rendered difficult by the absence of efficient segmentation tools. Thus, specialized software for the computation of 3D maps by EFTEM needs to include optimized methods for image series alignment, algorithms to improve SNR, different background subtraction models, and methods to facilitate map segmentation. Here we present a software package (EFTEM-TomoJ, which can be downloaded from http://u759.curie.fr/fr/download/softwares/EFTEM-TomoJ ), specifically dedicated to computation of EFTEM 3D chemical maps including noise filtering by image reconstitution based on multivariate statistical analysis. We also present an algorithm named BgART (for background removing algebraic reconstruction technique) allowing the discrimination between background and signal and improving the reconstructed volume in an iterative way.

Apa Reference Messaoudi, C., Aschman, N., Cunha, M., Oikawa, T., Sorzano, C.O.S. & Marco, S. (2013). Three-Dimensional Chemical Mapping by EFTEM-TomoJ Including Improvement of SNR by PCA and ART Reconstruction of Volume by Noise Suppression. Microscopy and Microanalysis, 19(6), 1669-1677. 10.1017/S1431927613013317
Doi 10.1017/S1431927613013317
Publication Date 28 Aug 2013
Publication Type Article
Researcher Carlos Oscar Sorzano
Ontology Bioinformatics Software and Tools, Experimental structure determination, Mapping, Multivariate statistics, Dimensionality reduction
Research Groups
Tools

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