Volumetric quantification of atherosclerotic plaque in CT considering partial volume effect.

Details

Serval ID
serval:BIB_205726168013
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Volumetric quantification of atherosclerotic plaque in CT considering partial volume effect.
Journal
IEEE transactions on medical imaging
Author(s)
Dehmeshki J., Ye X., Amin H., Abaei M., Lin X., Qanadli S.D.
ISSN
0278-0062
Publication state
Published
Issued date
2007
Peer-reviewed
Oui
Volume
26
Number
3
Pages
273-82
Language
english
Notes
Publication types: Evaluation Studies ; Journal Article - Publication Status: ppublish
Abstract
Coronary artery calcification (CAC) is quantified based on a computed tomography (CT) scan image. A calcified region is identified. Modified expectation maximization (MEM) of a statistical model for the calcified and background material is used to estimate the partial calcium content of the voxels. The algorithm limits the region over which MEM is performed. By using MEM, the statistical properties of the model are iteratively updated based on the calculated resultant calcium distribution from the previous iteration. The estimated statistical properties are used to generate a map of the partial calcium content in the calcified region. The volume of calcium in the calcified region is determined based on the map. The experimental results on a cardiac phantom, scanned 90 times using 15 different protocols, demonstrate that the proposed method is less sensitive to partial volume effect and noise, with average error of 9.5% (standard deviation (SD) of 5-7mm(3)) compared with 67% (SD of 3-20mm(3)) for conventional techniques. The high reproducibility of the proposed method for 35 patients, scanned twice using the same protocol at a minimum interval of 10 min, shows that the method provides 2-3 times lower interscan variation than conventional techniques.
Keywords
Algorithms, Calcinosis, Coronary Artery Disease, Humans, Imaging, Three-Dimensional, Phantoms, Imaging, Radiographic Image Enhancement, Radiographic Image Interpretation, Computer-Assisted, Reproducibility of Results, Sensitivity and Specificity, Tomography, X-Ray Computed
Pubmed
Web of science
Create date
11/04/2008 12:19
Last modification date
20/08/2019 12:56
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