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Proceedings Paper

Evaluation of nonlinear pre-sampled modulation transfer function in iterative reconstruction CT
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Paper Abstract

Iterative reconstruction (IR) technique is growingly used in clinical CT imaging with an expectation for improved image quality at lower patient doses. However, the nonlinear frequency response in different noise level and object contrast is less explored. In this study, we evaluate object contrast and dose level-dependent behavior of modulation transfer function in iterative reconstruction computed tomography imaging with a specially fabricated phantom. We created multi-contrast edge phantom, which consists of acrylic panel and diluted iodine contrast agent with different concentrations. Images were acquired with a multi-detector CT (Discovery CT750 HD: GE) at four dose levels (25, 50, 100 and 200mAs), and were reconstructed using FBP and two IR techniques (ASIR50 and VEO). Edge spread functions were extracted across angled edges on image, and were differentiated to yield line spread function. LSF were Fourier transformed to evaluate the presampled MTFs of IR and FBP reconstruction techniques. At same dose level (200mAs), the MTFs with higher contrast showed higher response than that of lower contrast in VEO. A MTF50 of 200mAs showed markedly higher responses up to 23% than that of 25mAs scan with VEO reconstruction for an edge phantom of 520HU contrast. Our study revealed that MTF of IR technique degrades depending on noise level at low dose scan. Therefore, we recommend that its characteristic should be considered in quantitative analysis such as lesion size measurement.

Paper Details

Date Published: 6 March 2013
PDF: 7 pages
Proc. SPIE 8668, Medical Imaging 2013: Physics of Medical Imaging, 86684P (6 March 2013); doi: 10.1117/12.2007823
Show Author Affiliations
Hyeong Min Jin, Seoul National Univ. (Korea, Republic of)
Jong Hyo Kim, Seoul National Univ. (Korea, Republic of)


Published in SPIE Proceedings Vol. 8668:
Medical Imaging 2013: Physics of Medical Imaging
Robert M. Nishikawa; Bruce R. Whiting; Christoph Hoeschen, Editor(s)

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