An algorithm for constrained one-step inversion of spectral CT data

作者：Barber Rina Foygel^*; Sidky Emil Y^*; Schmidt Taly Gilat^*; Pan Xiaochuan^*

来源：Physics in Medicine and Biology, 2016, 61(10): 3784-3818.

DOI：10.1088/0031-9155/61/10/3784

• spectral computed tomography
• iterative image reconstruction
• non-convex optimization
• total variation
• photon counting detection

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.

• 出版日期2016-5-21