What is it about?
X-ray sources are polychromatic. Ignoring this fact when performing reconstruction leads to artifacts, such as cupping and streaking, in reconstructed images. We first propose a new model parameterization that allows for blind correction of these artifacts and then develop reconstruction algorithms based on this parameterization. Here, blind correction means that we do not know - incident spectrum (which is an X-ray machine characteristic) and - mass attenuation (inspected material).
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Why is it important?
Why blind? Accurately characterizing X-ray machine and inspected material is not easy or may not be possible. The developed model and algorithms are applicable to nondestructive evaluation (NDE) and medical imaging. This topic is relevant to all X-ray CT applications.
Perspectives
Our NPG-BFGS algorithm is the first physical-model based image reconstruction method for simultaneous blind sparse image reconstruction and mass-attenuation spectrum estimation from polychromatic measurements. NPG-BFGS matches or outperforms non-blind linearization methods that assume perfect knowledge of the X-ray source and material properties. We have identified and quantified inherent limitations of the blind model, such as the shift ambiguity of the mass-attenuation spectrum. Interesting features: - Laplace-transform formulation of the noiseless measurements and generalized linear models (GLMs) that follow from this formulation, - conditions for biconvexity, - establishment of the Kurdyka-Łojasiewicz property, and - potential for extension to more general models.
Dr Aleksandar Dogandžić
Iowa State University
Read the Original
This page is a summary of: Blind X-Ray CT Image Reconstruction From Polychromatic Poisson Measurements, IEEE Transactions on Computational Imaging, June 2016, Institute of Electrical & Electronics Engineers (IEEE),
DOI: 10.1109/tci.2016.2523431.
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