Paper
2 September 2010 Reconstruction algorithms for laboratory microCT/microXRF system
Xuan Liu, Peter Bruyndonckx, Alexander Sasov
Author Affiliations +
Abstract
An integrated microCT/microXRF system has been designed and built at SkyScan. The two sub-systems are aligned. The microCT provides 3D morphological information of the sample, which can be also used for attenuation correction during microXRF reconstruction. The microXRF, based on a pin-hole collimator and a photon-counting energy-sensitive 2Ddetector, obtains 2D projections of 3D chemical composition inside the sample with 50-70 microns spatial resolution. The reconstruction of 3D microXRF scans is challenging because of very low photon counting statistics due to limited power of laboratory x-ray sources and the strong self-absorption of the low-energy fluorescence photons. We have developed a maximum-likelihood expectation-maximization (ML-EM) algorithm based on Poisson model. This algorithm has proven to be rather robust and good reconstructions have been obtained with sample scans. Regularization is necessary to achieve stable reconstruction. One method is to apply smoothing between iterations. Two different smoothing kernels have been evaluated: 3D symmetric Gaussian kernel and minimization of total variation. For further improvement, a multi-ray resolution recovery technique has been evaluated. The self-absorption is currently compensated by a simplified method: the correction coefficients are pre-calculated and obtained by forward-projecting the attenuation map for both the primary X-rays and the fluorescence photons. The attenuation maps at the energy of fluorescence photons are approximated from the CT image.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xuan Liu, Peter Bruyndonckx, and Alexander Sasov "Reconstruction algorithms for laboratory microCT/microXRF system", Proc. SPIE 7804, Developments in X-Ray Tomography VII, 780419 (2 September 2010); https://doi.org/10.1117/12.860541
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KEYWORDS
Signal attenuation

Expectation maximization algorithms

X-rays

Reconstruction algorithms

Imaging systems

Sensors

X-ray sources

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