Title

Sparse-View CT Reconstruction Based on Nonconvex L1 − L2 Regularizations

Document Type

Article

Publication Date

4-1-2017

Publication Title

International Scholarly and Scientific Research & Innovation

Volume

11

Issue

4

First page number:

472

Last page number:

475

Abstract

We present a nonconvex, Lipschitz continuous and non-smooth regularization model. The CT reconstruction is formulated as a nonconvex constrained L1 − L2 minimization problem and solved through a difference of convex algorithm and alternating direction of multiplier method which generates a better result than L0 or L1 regularizers in the CT reconstruction.

Keywords

Computed tomography, sparse-view reconstruction, L1 −L2 minimization, non-convex, difference of convex functions

Language

eng

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