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/

Zendy Open

Presents the pdf analysis as premium feature

PDF Analysis

Insights

Presents the summarisation as premium feature

Summarisation

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

The Bayes Inference Engine (BIE) has been used to perform a 4D reconstruction of a first-pass radiotracer bolus distribution inside a CardioWest Total Artificial Heart, imaged with the University of Arizona's FastSPECT system. The BIE estimates parameter values that define the 3D model of the radiotracer distribution at each of 41 times spanning about two seconds. The 3D models have two components: a closed surface, composed of bi-quadratic Bezier triangular surface patches, that defines the interface between the part of the blood pool that contains radiotracer and the part that contains no radiotracer, and smooth voxel-to-voxel variations in intensity within the closed surface. Ideally, the surface estimates the ventricular wall location where the bolus is infused throughout the part of the blood pool contained by the right ventricle. The voxel-to-voxel variations are needed to model an inhomogeneously-mixed bolus. Maximum a posterior (MAP) estimates of the Bezier control points and voxel values are obtained for each time frame. We show new reconstructions using the Bezier surface models, and discuss estimates of ventricular volume as a function of time, ejection fraction, and wall motion. The computation time for our reconstruction process, which directly estimates complex 3D model parameters from the raw data, is performed in a time that is competitive with more traditional voxel-based methods (ML-EM, e.g.).© (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

<title>4D reconstructions from low-count SPECT data using deformable models with smooth interior intensity variations</title>