title: An algorithm for constrained one-step inversion of spectral CT data.
abstract: We develop a primal-dual algorithm that allows for one-step inversion of spectral CT transmission photon counts data to a basis map decomposition. The algorithm allows for image constraints to be enforced on the basis maps during the inversion. The derivation of the algorithm makes use of a local upper bounding quadratic approximation to generate descent steps for non-convex spectral CT data discrepancy terms, combined with a new convex-concave optimization algorithm. Convergence of the algorithm is demonstrated on simulated spectral CT data. Simulations with noise and anthropomorphic phantoms show examples of how to employ the constrained one-step algorithm for spectral CT data.
authors.affiliation: Department of Statistics, The University of Chicago, 5734 S. University Ave., Chicago, IL 60637, USA.
authors.forename: Rina
authors.initials: R
authors.lastname: Foygel Barber
authors.forename: Emil Y
authors.initials: EY
authors.lastname: Sidky
authors.forename: Taly
authors.initials: T
authors.lastname: Gilat Schmidt
authors.forename: Xiaochuan
authors.initials: X
authors.lastname: Pan
mesh_terms: D000465:Algorithms; D019047:Phantoms, Imaging; D017785:Photons; D014057:Tomography, X-Ray Computed / Q000379:methods*