26 May 2016 Impact of number of repeated scans on model observer performance for a low-contrast detection task in computed tomography
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Abstract
Channelized Hotelling observer (CHO) models have been shown to correlate well with human observers for several phantom-based detection/classification tasks in clinical computed tomography (CT). A large number of repeated scans were used to achieve an accurate estimate of the model’s template. The purpose of this study is to investigate how the experimental and CHO model parameters affect the minimum required number of repeated scans. A phantom containing 21 low-contrast objects was scanned on a 128-slice CT scanner at three dose levels. Each scan was repeated 100 times. For each experimental configuration, the low-contrast detectability, quantified as the area under receiver operating characteristic curve, Az, was calculated using a previously validated CHO with randomly selected subsets of scans, ranging from 10 to 100. Using Az from the 100 scans as the reference, the accuracy from a smaller number of scans was determined. Our results demonstrated that the minimum number of repeated scans increased when the radiation dose level decreased, object size and contrast level decreased, and the number of channels increased. As a general trend, it increased as the low-contrast detectability decreased. This study provides a basis for the experimental design of task-based image quality assessment in clinical CT using CHO.
© 2016 Society of Photo-Optical Instrumentation Engineers (SPIE) 2329-4302/2016/$25.00 © 2016 SPIE
Chi Ma, Lifeng Yu, Baiyu Chen, Christopher Favazza, Shuai Leng, and Cynthia McCollough "Impact of number of repeated scans on model observer performance for a low-contrast detection task in computed tomography," Journal of Medical Imaging 3(2), 023504 (26 May 2016). https://doi.org/10.1117/1.JMI.3.2.023504
Published: 26 May 2016
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CITATIONS
Cited by 15 scholarly publications.
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KEYWORDS
Computed tomography

Performance modeling

Image quality

Infrared imaging

Optical filters

Infrared radiation

Diagnostics

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