Anthropomorphic model observer performance in three-dimensional detection task for low-contrast computed tomography

Alexandre H. Ba; Miguel P. Eckstein; Damien Racine; Julien G. Ott; Francis R. Verdun; Sabine Kobbe-Schmidt; François O. Bochud

doi:10.1117/1.JMI.3.1.011009

29 December 2015 Anthropomorphic model observer performance in three-dimensional detection task for low-contrast computed tomography

Alexandre H. Ba, Miguel P. Eckstein, Damien Racine, Julien G. Ott, Francis R. Verdun, Sabine Kobbe-Schmidt, François O. Bochud

Author Affiliations +

Journal of Medical Imaging, Vol. 3, Issue 1, 011009 (December 2015). https://doi.org/10.1117/1.JMI.3.1.011009

Abstract

X-ray medical imaging is increasingly becoming three-dimensional (3-D). The dose to the population and its management are of special concern in computed tomography (CT). Task-based methods with model observers to assess the dose-image quality trade-off are promising tools, but they still need to be validated for real volumetric images. The purpose of the present work is to evaluate anthropomorphic model observers in 3-D detection tasks for low-contrast CT images. We scanned a low-contrast phantom containing four types of signals at three dose levels and used two reconstruction algorithms. We implemented a multislice model observer based on the channelized Hotelling observer (msCHO) with anthropomorphic channels and investigated different internal noise methods. We found a good correlation for all tested model observers. These results suggest that the msCHO can be used as a relevant task-based method to evaluate low-contrast detection for CT and optimize scan protocols to lower dose in an efficient way.

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Alexandre H. Ba, Miguel P. Eckstein, Damien Racine, Julien G. Ott, Francis R. Verdun, Sabine Kobbe-Schmidt, and François O. Bochud "Anthropomorphic model observer performance in three-dimensional detection task for low-contrast computed tomography," Journal of Medical Imaging 3(1), 011009 (29 December 2015). https://doi.org/10.1117/1.JMI.3.1.011009

Published: 29 December 2015

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