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Assessment of a photon-counting detector for a dual-energy C-arm angiographic system:

Title
Assessment of a photon-counting detector for a dual-energy C-arm angiographic system:
Authors
Ahmad M.Fahrig R.Pung L.Spahn M.Köster N.S.Reitz S.Moore T.Choi J.-H.Hinshaw W.Xia Y.Müller K.
Ewha Authors
최장환
SCOPUS Author ID
최장환scopus
Issue Date
2017
Journal Title
Medical Physics
ISSN
0094-2405JCR Link
Citation
Medical Physics vol. 44, no. 11, pp. 5938 - 5948
Keywords
C-armcomputed tomographydual-energyphoton-countingx-ray detectors
Publisher
John Wiley and Sons Ltd.
Indexed
SCIE; SCOPUS WOS scopus
Document Type
Article
Abstract
Purpose: This article presents the implementation and assessment of photon-counting dual-energy x-ray detector technology for angiographic C-arm systems in interventional radiology. Methods: A photon-counting detector was successfully integrated into a clinical C-arm CT system. Detector performance was assessed using image uniformity metrics in both 2D projections and 3D cone-beam computed tomography (CBCT) images. Uniform exposure fields were acquired to analyze projection images and scans of a homogeneous cylinder phantom were taken to analyze 3D reconstructions. Image uniformity was assessed over a broad range of imaging parameters. Results: Detector calibration greatly improved image uniformity, reducing image variation from 8.8% to 0.5% in an ideal scenario, but image uniformity degraded when imaging parameters varied strongly from values set at calibration: the tube voltage, low-high energy threshhold, and tube current had the greatest impact. Material discrimination and dynamic angiography capabilities were successfully demonstrated in separate phantom and in vivo experiments. Conclusion: The uniformity results identified major factors degrading image quality. The quantitative results will guide selection of calibration points to mitigate the loss of uniformity. The unique combination of dual-energy and fluoroscopy imaging capabilities with a flat-panel photon-counting detector may enable new applications in interventional radiology. © 2017 American Association of Physicists in Medicine.
DOI
10.1002/mp.12517
Appears in Collections:
인공지능대학 > 인공지능학과 > Journal papers
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