Campus Units

Electrical and Computer Engineering

Document Type

Conference Proceeding

Conference

41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016)

Publication Version

Accepted Manuscript

Publication Date

2016

Conference Title

IEEE International Conference on Acoustics, Speech and Signal Processing

Conference Date

March 20-25, 2016

City

Shanghai, China

Abstract

We develop a sparse image reconstruction method for Poissondistributed polychromatic X-ray computed tomography (CT) measurements under the blind scenario where the material of the inspected object and the incident energy spectrum are unknown. We employ our mass-attenuation spectrum parameterization of the noiseless measurements for single-material objects and express the mass-attenuation spectrum as a linear combination of B-spline basis functions of order one. A block coordinatedescent algorithm is developed for constrained minimization of a penalized Poisson negative log-likelihood (NLL) cost function, where constraints and penalty terms ensure nonnegativity of the spline coefficients and nonnegativity and sparsity of the density-map image; the image sparsity is imposed using a convex total-variation (TV) norm penalty term. This algorithm alternates between a Nesterov’s proximal-gradient (NPG) step for estimating the density-map image and a limited-memory Broyden-Fletcher-Goldfarb-Shanno with box constraints (LBFGS- B) step for estimating the incident-spectrum parameters. We establish conditions for biconvexity of the penalized NLL objective function, which, if satisfied, ensures monotonicity of the NPG-BFGS iteration. We also show that the penalized NLL objective satisfies the Kurdyka-Łojasiewicz property, which is important for establishing local convergence of block-coordinate descent schemes in biconvex optimization problems. Simulation examples demonstrate the performance of the proposed scheme.

Comments

This is the accepted manuscript of a proceeding from the 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016), Paper BISP-P4.8, March 20-25, 2016, Shanghai, China.

Copyright Owner

IEEE

Language

en

File Format

application/pdf

Share

Article Location

 
COinS