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

Anthropomorphic model observer performance in three-dimensional detection task for low-contrast... 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Medical Imaging SPIE

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

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


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. © 2015 Society of Photo-Optical Instrumentation Engineers (SPIE) Keywords: three-dimensional analysis technique; computed tomography; image quality; model observer; observer performance evaluation; volumetric imaging. Paper 15163SSPR received Aug. 17, 2015; accepted for publication Nov. 23, 2015; published online Dec. 29, 2015. Introduction For several decades, x-ray medical imaging has been evolving into 3-D, in particular with the advent of computed tomography (CT). The expansion to volumetric body data has resulted in more accurate diagnosis1,2 but inevitably induced a higher radiation dose to the patient compared to equivalent twodimensional (2-D) techniques. Furthermore, the number of CT devices and examinations performed on patients is increasing, raising concerns about the mean population dose and necessitating increased management of the radiological process.3,4 However, the radiological process can be optimized only with a simultaneous consideration...
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Publisher
SPIE
Copyright
© 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)
Subject
Special Section on Medical Image Perception and Observer Performance; Paper
ISSN
2329-4302
eISSN
2329-4310
DOI
10.1117/1.JMI.3.1.011009
pmid
26719849
Publisher site
See Article on Publisher Site

Abstract

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.

Journal

Journal of Medical ImagingSPIE

Published: Jan 1, 2016

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