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A methodology for image quality evaluation of advanced CT systems.

Publication ,  Journal Article
Wilson, JM; Christianson, OI; Richard, S; Samei, E
Published in: Med Phys
March 2013

PURPOSE: This work involved the development of a phantom-based method to quantify the performance of tube current modulation and iterative reconstruction in modern computed tomography (CT) systems. The quantification included resolution, HU accuracy, noise, and noise texture accounting for the impact of contrast, prescribed dose, reconstruction algorithm, and body size. METHODS: A 42-cm-long, 22.5-kg polyethylene phantom was designed to model four body sizes. Each size was represented by a uniform section, for the measurement of the noise-power spectrum (NPS), and a feature section containing various rods, for the measurement of HU and the task-based modulation transfer function (TTF). The phantom was scanned on a clinical CT system (GE, 750HD) using a range of tube current modulation settings (NI levels) and reconstruction methods (FBP and ASIR30). An image quality analysis program was developed to process the phantom data to calculate the targeted image quality metrics as a function of contrast, prescribed dose, and body size. RESULTS: The phantom fabrication closely followed the design specifications. In terms of tube current modulation, the tube current and resulting image noise varied as a function of phantom size as expected based on the manufacturer specification: From the 16- to 37-cm section, the HU contrast for each rod was inversely related to phantom size, and noise was relatively constant (<5% change). With iterative reconstruction, the TTF exhibited a contrast dependency with better performance for higher contrast objects. At low noise levels, TTFs of iterative reconstruction were better than those of FBP, but at higher noise, that superiority was not maintained at all contrast levels. Relative to FBP, the NPS of iterative reconstruction exhibited an ~30% decrease in magnitude and a 0.1 mm(-1) shift in the peak frequency. CONCLUSIONS: Phantom and image quality analysis software were created for assessing CT image quality over a range of contrasts, doses, and body sizes. The testing platform enabled robust NPS, TTF, HU, and pixel noise measurements as a function of body size capable of characterizing the performance of reconstruction algorithms and tube current modulation techniques.

Duke Scholars

Published In

Med Phys

DOI

EISSN

2473-4209

Publication Date

March 2013

Volume

40

Issue

3

Start / End Page

031908

Location

United States

Related Subject Headings

  • Tomography, X-Ray Computed
  • Signal-To-Noise Ratio
  • Quality Control
  • Polyethylene
  • Phantoms, Imaging
  • Nuclear Medicine & Medical Imaging
  • Image Processing, Computer-Assisted
  • Body Size
  • 5105 Medical and biological physics
  • 4003 Biomedical engineering
 

Citation

APA
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ICMJE
MLA
NLM
Wilson, J. M., Christianson, O. I., Richard, S., & Samei, E. (2013). A methodology for image quality evaluation of advanced CT systems. Med Phys, 40(3), 031908. https://doi.org/10.1118/1.4791645
Wilson, Joshua M., Olav I. Christianson, Samuel Richard, and Ehsan Samei. “A methodology for image quality evaluation of advanced CT systems.Med Phys 40, no. 3 (March 2013): 031908. https://doi.org/10.1118/1.4791645.
Wilson JM, Christianson OI, Richard S, Samei E. A methodology for image quality evaluation of advanced CT systems. Med Phys. 2013 Mar;40(3):031908.
Wilson, Joshua M., et al. “A methodology for image quality evaluation of advanced CT systems.Med Phys, vol. 40, no. 3, Mar. 2013, p. 031908. Pubmed, doi:10.1118/1.4791645.
Wilson JM, Christianson OI, Richard S, Samei E. A methodology for image quality evaluation of advanced CT systems. Med Phys. 2013 Mar;40(3):031908.

Published In

Med Phys

DOI

EISSN

2473-4209

Publication Date

March 2013

Volume

40

Issue

3

Start / End Page

031908

Location

United States

Related Subject Headings

  • Tomography, X-Ray Computed
  • Signal-To-Noise Ratio
  • Quality Control
  • Polyethylene
  • Phantoms, Imaging
  • Nuclear Medicine & Medical Imaging
  • Image Processing, Computer-Assisted
  • Body Size
  • 5105 Medical and biological physics
  • 4003 Biomedical engineering