Title
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Low-dose micro-CT imaging for vascular segmentation and analysis using sparse-view acquisitions
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Author
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Abstract
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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. |
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Language
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English
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Source (journal)
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PLoS ONE
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Publication
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2013
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ISSN
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1932-6203
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DOI
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10.1371/JOURNAL.PONE.0068449
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Volume/pages
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8
:7
(2013)
, p. 1-10
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Article Reference
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e68449
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ISI
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000321271900032
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Medium
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E-only publicatie
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Full text (Publisher's DOI)
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Full text (open access)
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