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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In this paper we study the reconstruction of moving object densities fromundersampled dynamic X-ray tomography in two dimensions. A particularmotivation of this study is to use realistic measurement protocols forpractical applications, i.e. we do not assume to have a full Radon transform ineach time step, but only projections in few angular directions. Thisrestriction enforces a space-time reconstruction, which we perform byincorporating physical motion models and regularization of motion vectors in avariational framework. The methodology of optical flow, which is one of themost common methods to estimate motion between two images, is utilized toformulate a joint variational model for reconstruction and motion estimation.  We provide a basic mathematical analysis of the forward model and thevariational model for the image reconstruction. Moreover, we discuss theefficient numerical minimization based on alternating minimizations betweenimages and motion vectors. A variety of results are presented for simulated andreal measurement data with different sampling strategy. A key observation isthat random sampling combined with our model allows reconstructions of similaramount of measurements and quality as a single static reconstruction.

A Variational Reconstruction Method for Undersampled Dynamic X-ray Tomography based on Physical Motion Models