English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In this paper we present a new two-level iterative algorithm for tomographicimage reconstruction. The algorithm uses a regularization technique, which wecall edge-preserving Laplacian, that preserves sharp edges between objectswhile damping spurious oscillations in the areas where the reconstructed imageis smooth. Our numerical simulations demonstrate that the proposed methodoutperforms total variation (TV) regularization and it is competitive with thecombined TV-L2 penalty. Obtained reconstructed images show increasedsignal-to-noise ratio and visually appealing structural features. Computerimplementation and parameter control of the proposed technique isstraightforward, which increases the feasibility of it across many tomographicapplications. In this paper, we applied our method to the under-sampledcomputed tomography (CT) projection data and also considered a case ofreconstruction in emission tomography The MATLAB code is provided to supportobtained results.

Direct high-order edge-preserving regularization for tomographic image reconstruction