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

Improving the quality of positron emission tomography (PET) images, affectedby low resolution and high level of noise, is a challenging task in nuclearmedicine and radiotherapy. This work proposes a restoration method, achievedafter tomographic reconstruction of the images and targeting clinicalsituations where raw data are often not accessible. Based on inverse problemmethods, our contribution introduces the recently developed total generalizedvariation (TGV) norm to regularize PET image deconvolution. Moreover, westabilize this procedure with additional image constraints such as positivityand photometry invariance. A criterion for updating and adjusting automaticallythe regularization parameter in case of Poisson noise is also presented.Experiments are conducted on both synthetic data and real patient images.

Post-Reconstruction Deconvolution of PET Images by Total Generalized Variation Regularization