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Proceedings Paper

Image quality based x-ray dose control in cardiac imaging
Author(s): Andrew G. Davies; Stephen M. Kengyelics; Amber J. Gislason-Lee
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Paper Abstract

An automated closed-loop dose control system balances the radiation dose delivered to patients and the quality of images produced in cardiac x-ray imaging systems. Using computer simulations, this study compared two designs of automatic x-ray dose control in terms of the radiation dose and quality of images produced. The first design, commonly in x-ray systems today, maintained a constant dose rate at the image receptor. The second design maintained a constant image quality in the output images. A computer model represented patients as a polymethylmetacrylate phantom (which has similar x-ray attenuation to soft tissue), containing a detail representative of an artery filled with contrast medium. The model predicted the entrance surface dose to the phantom and contrast to noise ratio of the detail as an index of image quality. Results showed that for the constant dose control system, phantom dose increased substantially with phantom size (x5 increase between 20 cm and 30 cm thick phantom), yet the image quality decreased by 43% for the same thicknesses. For the constant quality control, phantom dose increased at a greater rate with phantom thickness (>x10 increase between 20 cm and 30 cm phantom). Image quality based dose control could tailor the x-ray output to just achieve the quality required, which would reduce dose to patients where the current dose control produces images of too high quality. However, maintaining higher levels of image quality for large patients would result in a significant dose increase over current practice.

Paper Details

Date Published: 16 March 2015
PDF: 8 pages
Proc. SPIE 9399, Image Processing: Algorithms and Systems XIII, 93990E (16 March 2015); doi: 10.1117/12.2082795
Show Author Affiliations
Andrew G. Davies, Univ. of Leeds (United Kingdom)
Stephen M. Kengyelics, Univ. of Leeds (United Kingdom)
Amber J. Gislason-Lee, Univ. of Leeds (United Kingdom)


Published in SPIE Proceedings Vol. 9399:
Image Processing: Algorithms and Systems XIII
Karen O. Egiazarian; Sos S. Agaian; Atanas P. Gotchev, Editor(s)

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