Document Type

Conference Proceeding

Conference

2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2013

Publication Date

12-2013

City

Saint Martin

Abstract

We develop a nonlinear sparse X-ray computed tomography (CT) image reconstruction method that accounts for beam hardening effects due to polychromatic X-ray sources. We adopt the blind scenario where the material of the inspected object and the incident polychromatic source spectrum are unknown and apply mass attenuation discretization of the underlying integral expressions that model the noiseless measurements. Our reconstruction algorithm employs constrained minimization of a penalized least-squares cost function, where nonnegativity and maximum-energy constraints are imposed on incident spectrum parameters and negative-energy and smooth ℓ1-norm penalty terms are introduced to ensure the nonnegativity and sparsity of the density map image. This minimization scheme alternates between a nonlinear conjugate-gradient step for estimating the density map image and an active set step for estimating incident spectrum parameters. We compare the proposed method with the existing approaches, which ignore the polychromatic nature of the measurements or sparsity of the density map image.

Comments

This is a manuscript of an article from 2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2013, 4pp.

Copyright Owner

Renliang Gu and Aleksandar Dogandžić

Language

en

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