Imperial College London
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ProfessorMartinBlunt

Faculty of Engineering, Department of Earth Science & Engineering

Chair in Flow in Porous Media
 
 
 
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Contact

 

+44 (0)20 7594 6500m.blunt Website

 
 
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Location

 

2.38ARoyal School of MinesSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Lin:2018:10.1016/j.advwatres.2018.03.007,
author = {Lin, Q and Andrew, M and Thompson, W and Blunt, MJ and Bijeljic, B},
doi = {10.1016/j.advwatres.2018.03.007},
journal = {Advances in Water Resources},
pages = {112--124},
title = {Optimization of image quality and acquisition time for lab-based X-ray microtomography using an iterative reconstruction algorithm},
url = {http://dx.doi.org/10.1016/j.advwatres.2018.03.007},
volume = {115},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - © 2018 The Authors Non-invasive laboratory-based X-ray microtomography has been widely applied in many industrial and research disciplines. However, the main barrier to the use of laboratory systems compared to a synchrotron beamline is its much longer image acquisition time (hours per scan compared to seconds to minutes at a synchrotron), which results in limited application for dynamic in situ processes. Therefore, the majorit y of existing laboratory X-ray microtomography is limited to static imaging; relatively fast imaging (tens of minutes per scan) can only be achieved by sacrificing imaging quality, e.g. reducing exposure time or number of projections. To alleviate this barrier, we introduce an optimized implementation of a well-known iterative reconstruction algorithm that allows users to reconstruct tomographic images with reasonable image quality, but requires lower X-ray signal counts and fewer projections than conventional methods. Quantitative analysis and comparison between the iterative and the conventional filtered back-projection reconstruction algorithm was performed using a sandstone rock sample with and without liquid phases in the pore space. Overall, by implementing the iterative reconstruction algorithm, the required image acquisition time for samples such as this, with sparse object structure, can be reduced by a factor of up to 4 without measurable loss of sharpness or signal to noise ratio.
AU  - Lin,Q
AU  - Andrew,M
AU  - Thompson,W
AU  - Blunt,MJ
AU  - Bijeljic,B
DO  - 10.1016/j.advwatres.2018.03.007
EP  - 124
PY  - 2018///
SN  - 0309-1708
SP  - 112
TI  - Optimization of image quality and acquisition time for lab-based X-ray microtomography using an iterative reconstruction algorithm
T2  - Advances in Water Resources
UR  - http://dx.doi.org/10.1016/j.advwatres.2018.03.007
UR  - http://hdl.handle.net/10044/1/58454
VL  - 115
ER  -
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