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Title: Hyperspectral image reconstruction for x-ray fluorescence tomography

Abstract

A penalized maximum-likelihood estimation is proposed to perform hyperspectral (spatio-spectral) image reconstruction for X-ray fluorescence tomography. The approach minimizes a Poisson-based negative log-likelihood of the observed photon counts, and uses a penalty term that has the effect of encouraging local continuity of model parameter estimates in both spatial and spectral dimensions simultaneously. The performance of the reconstruction method is demonstrated with experimental data acquired from a seed of arabidopsis thaliana collected at the 13-ID-E microprobe beamline at the Advanced Photon Source. The resulting element distribution estimates with the proposed approach show significantly better reconstruction quality than the conventional analytical inversion approaches, and allows for a high data compression factor which can reduce data acquisition times remarkably. In particular, this technique provides the capability to tomographically reconstruct full energy dispersive spectra without compromising reconstruction artifacts that impact the interpretation of results.

Authors:
; ; ; ;
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
National Science Foundation (NSF) - Directorate for Geosciences Division of Earth Sciences (GEO/EAR); USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1392113
DOE Contract Number:  
AC02-06CH11357
Resource Type:
Journal Article
Journal Name:
Optics Express
Additional Journal Information:
Journal Volume: 23; Journal Issue: 7; Journal ID: ISSN 1094-4087
Publisher:
Optical Society of America (OSA)
Country of Publication:
United States
Language:
English
Subject:
Fluorescence microscopy; Image reconstruction techniques; Inverse problems; Tomographic image processing

Citation Formats

Gürsoy, Doǧa, Biçer, Tekin, Lanzirotti, Antonio, Newville, Matthew G., and De Carlo, Francesco. Hyperspectral image reconstruction for x-ray fluorescence tomography. United States: N. p., 2015. Web. doi:10.1364/OE.23.009014.
Gürsoy, Doǧa, Biçer, Tekin, Lanzirotti, Antonio, Newville, Matthew G., & De Carlo, Francesco. Hyperspectral image reconstruction for x-ray fluorescence tomography. United States. https://doi.org/10.1364/OE.23.009014
Gürsoy, Doǧa, Biçer, Tekin, Lanzirotti, Antonio, Newville, Matthew G., and De Carlo, Francesco. 2015. "Hyperspectral image reconstruction for x-ray fluorescence tomography". United States. https://doi.org/10.1364/OE.23.009014.
@article{osti_1392113,
title = {Hyperspectral image reconstruction for x-ray fluorescence tomography},
author = {Gürsoy, Doǧa and Biçer, Tekin and Lanzirotti, Antonio and Newville, Matthew G. and De Carlo, Francesco},
abstractNote = {A penalized maximum-likelihood estimation is proposed to perform hyperspectral (spatio-spectral) image reconstruction for X-ray fluorescence tomography. The approach minimizes a Poisson-based negative log-likelihood of the observed photon counts, and uses a penalty term that has the effect of encouraging local continuity of model parameter estimates in both spatial and spectral dimensions simultaneously. The performance of the reconstruction method is demonstrated with experimental data acquired from a seed of arabidopsis thaliana collected at the 13-ID-E microprobe beamline at the Advanced Photon Source. The resulting element distribution estimates with the proposed approach show significantly better reconstruction quality than the conventional analytical inversion approaches, and allows for a high data compression factor which can reduce data acquisition times remarkably. In particular, this technique provides the capability to tomographically reconstruct full energy dispersive spectra without compromising reconstruction artifacts that impact the interpretation of results.},
doi = {10.1364/OE.23.009014},
url = {https://www.osti.gov/biblio/1392113}, journal = {Optics Express},
issn = {1094-4087},
number = 7,
volume = 23,
place = {United States},
year = {Thu Jan 01 00:00:00 EST 2015},
month = {Thu Jan 01 00:00:00 EST 2015}
}

Works referenced in this record:

X-ray fluorescence microprobe imaging in biology and medicine
journal, January 2006


Localization of Iron in Arabidopsis Seed Requires the Vacuolar Membrane Transporter VIT1
journal, November 2006


Trends in hard X-ray fluorescence mapping: environmental applications in the age of fast detectors
journal, March 2011


Synchrotron X-Ray Microfluorescence and Microspectroscopy: Application and Perspectives in Materials Science
journal, November 2005


Hard X-ray fluorescence tomography—an emerging tool for structural visualization
journal, October 2010


X-ray phase contrast and fluorescence nanotomography for material studies
journal, January 2012

  • Suhonen, Heikki; Xu, Feng; Helfen, Lukas
  • International Journal of Materials Research (formerly Zeitschrift fuer Metallkunde), Vol. 103, Issue 02
  • https://doi.org/10.3139/146.110664

Laboratory x-ray fluorescence tomography for high-resolution nanoparticle bio-imaging
journal, January 2014


The Bionanoprobe: hard X-ray fluorescence nanoprobe with cryogenic capabilities
journal, December 2013


Spectral curve fitting for automatic hyperspectral data analysis
journal, June 2006


The MARTE VNIR Imaging Spectrometer Experiment: Design and Analysis
journal, October 2008


Developments in synchrotron x-ray computed microtomography at the National Synchrotron Light Source
conference, September 1999

  • Dowd, Betsy A.; Campbell, Graham H.; Marr, Robert B.
  • SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, SPIE Proceedings
  • https://doi.org/10.1117/12.363725

X-ray fluorescent computer tomography with synchrotron radiation
journal, January 1998


Monotonic penalized-likelihood image reconstruction for X-ray fluorescence computed tomography
journal, September 2006


Reduced-Scan Schemes for X-Ray Fluorescence Computed Tomography
journal, October 2007


Iterative reconstruction techniques in emission computed tomography
journal, July 2006


Iterative Reconstruction in X-ray Fluorescence Tomography Based on Radon Inversion
journal, February 2011


Penalized-likelihood image reconstruction for x-ray fluorescence computed tomography
journal, July 2006


Reconstructing x-ray fluorescence microtomograms
journal, September 2001


Internal elemental microanalysis combining x-ray fluorescence, Compton and transmission tomography
journal, July 2003


A Maximum a Posteriori Probability Expectation Maximization Algorithm for Image Reconstruction in Emission Tomography
journal, September 1987


Gibbs and Markov random systems with constraints
journal, January 1974


Convergence of EM image reconstruction algorithms with Gibbs smoothing
journal, January 1990


Regularized Image Reconstruction Algorithms for Positron Emission Tomography
journal, September 2004


Scientific data exchange: a schema for HDF5-based storage of raw and analyzed data
journal, October 2014


TomoPy: a framework for the analysis of synchrotron tomographic data
journal, August 2014


Works referencing / citing this record:

2016 Atomic Spectrometry Update – a review of advances in X-ray fluorescence spectrometry and its applications
journal, January 2016


Automatic processing of multimodal tomography datasets
journal, January 2017


Trace: a high-throughput tomographic reconstruction engine for large-scale datasets
journal, January 2017


Joint reconstruction of x-ray fluorescence and transmission tomography
journal, January 2017


Optimization-based simultaneous alignment and reconstruction in multi-element tomography
journal, January 2019