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

There are several important positron emission tomography (PET) imaging scenarios that require imaging with very low photon statistics, for which both quantitative accuracy and visual quality should not be neglected. For example, PET imaging with the low photon statistics is closely related to active efforts to significantly reduce radiation exposure from radiopharmaceuticals. We investigated two examples of low-count PET imaging: (a) imaging [ 90 Y]microsphere radioembolization that suffers the very small positron emission fraction of Y-90's decay processes, and (b) cancer imaging with [ 68 Ga]citrate with uptake time of 3-4 half-lives, necessary for visualizing tumors. In particular, we investigated a type of penalized likelihood reconstruction algorithm, block sequential regularized expectation maximization (BSREM), for improving both image quality and quantitative accuracy of these low-count PET imaging cases.

molecular imaging and biology

Quantitative and Qualitative Improvement of Low-Count [68Ga]Citrate and [90Y]Microspheres PET Image Reconstructions Using Block Sequential Regularized Expectation Maximization Algorithm