Regularization designs for uniform spatial resolution and noise properties in statistical image reconstruction for 3-D X-ray CT.

ABSTRACT: Statistical image reconstruction methods for X-ray computed tomography (CT) provide improved spatial resolution and noise properties over conventional filtered back-projection (FBP) reconstruction, along with other potential advantages such as reduced patient dose and artifacts. Conventional regularized image reconstruction leads to spatially variant spatial resolution and noise characteristics because of interactions between the system models and the regularization. Previous regularization design methods aiming to solve such issues mostly rely on circulant approximations of the Fisher information matrix that are very inaccurate for undersampled geometries like short-scan cone-beam CT. This paper extends the regularization method proposed in to 3-D cone-beam CT by introducing a hypothetica

SUBMITTER: Cho JH 

PROVIDER: S-EPMC4315750 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature