Implementation of a Phase Detection Algorithm for Dynamic Cardiac Computed Tomography Analysis Based on Time Dependent Contrast Agent Distribution
Author(s) -
Carsten Kendziorra,
Henning Meyer,
Marc Dewey
Publication year - 2014
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0116103
Subject(s) - contrast (vision) , algorithm , ventricle , computer science , phase contrast microscopy , computed tomography , perfusion , phase (matter) , artificial intelligence , radiology , medicine , physics , cardiology , quantum mechanics , optics
This paper presents a phase detection algorithm for four-dimensional (4D) cardiac computed tomography (CT) analysis. The algorithm detects a phase, i.e. a specific three-dimensional (3D) image out of several time-distributed 3D images, with high contrast in the left ventricle and low contrast in the right ventricle. The purpose is to use the automatically detected phase in an existing algorithm that automatically aligns the images along the heart axis. Decision making is based on the contrast agent distribution over time. It was implemented in KardioPerfusion – a software framework currently being developed for 4D CT myocardial perfusion analysis. Agreement of the phase detection algorithm with two reference readers was 97% (95% CI: 82–100%). Mean duration for detection was 0.020 s (95% CI: 0.018–0.022 s), which wastimes less than the readers needed ( s,). Thus, this algorithm is an accurate and fast tool that can improve work flow of clinical examinations.
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