NACVMED-PHApr 26, 2014

Sinogram constrained TV-minimization for metal artifact reduction in CT

arXiv:1404.6691v15 citations
Originality Synthesis-oriented
AI Analysis

This addresses image quality issues in medical CT scans for healthcare applications, but it is incremental as it builds on existing optimization and regularization techniques.

The paper tackled metal artifacts in CT images by solving a convex optimization problem with sinogram constraints and total variation regularization, achieving artifact reduction as demonstrated on synthetic data.

A new method for reducing metal artifacts in X-ray computed tomography (CT) images is presented. It bases on the solution of a convex optimization problem with inequality constraints on the sinogram, and total variation regularization for the reconstructed image. The Chambolle-Pock algorithm is used to numerically solve the discretized version of the optimization problem. As proof of concept we present and discuss numerical results for synthetic data.

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