Title
Low-dose micro-CT imaging for vascular segmentation and analysis using sparse-view acquisitions Low-dose micro-CT imaging for vascular segmentation and analysis using sparse-view acquisitions
Author
Faculty/Department
Faculty of Medicine and Health Sciences
Publication type
article
Publication
Subject
Engineering sciences. Technology
Source (journal)
PLoS ONE
Volume/pages
8(2013) :7 , p. 1-10
ISSN
1932-6203
Article Reference
e68449
Carrier
E-only publicatie
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
The aim of this study is to investigate whether reliable and accurate 3D geometrical models of the murine aortic arch can be constructed from sparse-view data in vivo micro-CT acquisitions. This would considerably reduce acquisition time and X-ray dose. In vivo contrast-enhanced micro-CT datasets were reconstructed using a conventional filtered back projection algorithm (FDK), the image space reconstruction algorithm (ISRA) and total variation regularized ISRA (ISRA-TV). The reconstructed images were then semi-automatically segmented. Segmentations of high-and low-dose protocols were compared and evaluated based on voxel classification, 3D model diameters and centerline differences. FDK reconstruction does not lead to accurate segmentation in the case of low-view acquisitions. ISRA manages accurate segmentation with 1024 or more projection views. ISRA-TV needs a minimum of 256 views. These results indicate that accurate vascular models can be obtained from micro-CT scans with 8 times less X-ray dose and acquisition time, as long as regularized iterative reconstruction is used.
Full text (open access)
https://repository.uantwerpen.be/docman/irua/babdfe/5382.pdf
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