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Title: 3D reconstruction of the magnetic vector potential using model based iterative reconstruction

Abstract

Lorentz transmission electron microscopy (TEM) observations of magnetic nanoparticles contain information on the magnetic and electrostatic potentials. Vector field electron tomography (VFET) can be used to reconstruct electromagnetic potentials of the nanoparticles from their corresponding LTEM images. The VFET approach is based on the conventional filtered back projection approach to tomographic reconstructions and the availability of an incomplete set of measurements due to experimental limitations means that the reconstructed vector fields exhibit significant artifacts. In this paper, we outline a model-based iterative reconstruction (MBIR) algorithm to reconstruct the magnetic vector potential of magnetic nanoparticles. We combine a forward model for image formation in TEM experiments with a prior model to formulate the tomographic problem as a maximum a-posteriori probability estimation problem (MAP). The MAP cost function is minimized iteratively to determine the vector potential. As a result, a comparative reconstruction study of simulated as well as experimental data sets show that the MBIR approach yields quantifiably better reconstructions than the VFET approach.

Authors:
 [1];  [2];  [3];  [4];  [1]
+ Show Author Affiliations
  1. Carnegie Mellon Univ., Pittsburgh, PA (United States)
  2. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  3. Argonne National Lab. (ANL), Lemont, IL (United States)
  4. Purdue Univ., West Lafayette, IN (United States)
Publication Date:
Research Org.:
Argonne National Laboratory (ANL), Argonne, IL (United States); Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22), Materials Sciences and Engineering Division; National Science Foundation (NSF); USDOE
OSTI Identifier:
1378366
Alternate Identifier(s):
OSTI ID: 1411706; OSTI ID: 1550246
Report Number(s):
LLNL-JRNL-733823
Journal ID: ISSN 0304-3991; 136121
Grant/Contract Number:  
AC02-06CH11357; AC52-07NA27344; FG02-01ER45893
Resource Type:
Accepted Manuscript
Journal Name:
Ultramicroscopy
Additional Journal Information:
Journal Volume: 182; Journal Issue: C; Journal ID: ISSN 0304-3991
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; Lorentz microscopy; Model based iterative reconstruction (MBIR); Phase shift; Vector field electron tomography (VFET); 97 MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; 42 ENGINEERING

Citation Formats

Prabhat, K. C., Aditya Mohan, K., Phatak, Charudatta, Bouman, Charles, and De Graef, Marc. 3D reconstruction of the magnetic vector potential using model based iterative reconstruction. United States: N. p., 2017. Web. doi:10.1016/j.ultramic.2017.07.005.
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Prabhat, K. C., Aditya Mohan, K., Phatak, Charudatta, Bouman, Charles, & De Graef, Marc. 3D reconstruction of the magnetic vector potential using model based iterative reconstruction. United States. https://doi.org/10.1016/j.ultramic.2017.07.005
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Prabhat, K. C., Aditya Mohan, K., Phatak, Charudatta, Bouman, Charles, and De Graef, Marc. Mon . "3D reconstruction of the magnetic vector potential using model based iterative reconstruction". United States. https://doi.org/10.1016/j.ultramic.2017.07.005. https://www.osti.gov/servlets/purl/1378366.
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@article{osti_1378366,
title = {3D reconstruction of the magnetic vector potential using model based iterative reconstruction},
author = {Prabhat, K. C. and Aditya Mohan, K. and Phatak, Charudatta and Bouman, Charles and De Graef, Marc},
abstractNote = {Lorentz transmission electron microscopy (TEM) observations of magnetic nanoparticles contain information on the magnetic and electrostatic potentials. Vector field electron tomography (VFET) can be used to reconstruct electromagnetic potentials of the nanoparticles from their corresponding LTEM images. The VFET approach is based on the conventional filtered back projection approach to tomographic reconstructions and the availability of an incomplete set of measurements due to experimental limitations means that the reconstructed vector fields exhibit significant artifacts. In this paper, we outline a model-based iterative reconstruction (MBIR) algorithm to reconstruct the magnetic vector potential of magnetic nanoparticles. We combine a forward model for image formation in TEM experiments with a prior model to formulate the tomographic problem as a maximum a-posteriori probability estimation problem (MAP). The MAP cost function is minimized iteratively to determine the vector potential. As a result, a comparative reconstruction study of simulated as well as experimental data sets show that the MBIR approach yields quantifiably better reconstructions than the VFET approach.},
doi = {10.1016/j.ultramic.2017.07.005},
journal = {Ultramicroscopy},
number = C,
volume = 182,
place = {United States},
year = {Mon Jul 03 00:00:00 EDT 2017},
month = {Mon Jul 03 00:00:00 EDT 2017}
}
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