Predictive models for observer performance in CT: Applications in protocol optimization

Published

Journal Article

The relationship between theoretical descriptions of imaging performance (Fourier-based) and the performance of real human observers was investigated for detection tasks in multi-slice CT. The detectability index for the Fisher-Hotelling model observer and non-prewhitening model observer (with and without internal noise and eye filter) was computed using: 1) the measured modulation transfer function (MTF) and noise-power spectrum (NPS) for CT; and 2) a Fourier description of imaging task. Based upon CT images of human patients with added simulated lesions, human observer performance was assessed via an observer study in terms of the area under the ROC curve (Az). The degree to which the detectability index correlated with human observer performance was investigated and results for the non-prewhitening model observer with internal noise and eye filter (NPWE) were found to agree best with human performance over a broad range of imaging conditions. Results provided initial validation that CT image acquisition and reconstruction parameters can be optimized for observer performance rather than system performance (i.e., contrast-to-noise ratio, MTF, and NPS). The NPWE model was further applied for the comparison of FBP with a novel modelbased iterative reconstruction algorithm to assess its potential for dose reduction.

Full Text

Duke Authors

Cited Authors

  • Richard, S; Li, X; Yadava, G; Samei, E

Published Date

  • May 13, 2011

Published In

Volume / Issue

  • 7961 /

International Standard Serial Number (ISSN)

  • 1605-7422

Digital Object Identifier (DOI)

  • 10.1117/12.877069

Citation Source

  • Scopus