Image Perception, Observer Performance, and Technology Assessment

Correlation between human detection accuracy and observer model-based image quality metrics in computed tomography

[+] Author Affiliations
Justin Solomon

Duke University Health System, Department of Radiology, Carl E. Ravin Advanced Imaging Laboratories, 2424 Erwin Road, Suite 302, Durham, North Carolina 27705, United States

Ehsan Samei

Duke University Health System, Department of Radiology, Carl E. Ravin Advanced Imaging Laboratories, 2424 Erwin Road, Suite 302, Durham, North Carolina 27705, United States

Duke University Medical Center, Department of Radiology, Clinical Imaging Physics Group, 2424 Erwin Road, Suite 302, Durham, North Carolina 27705, United States

Duke University, Pratt School of Engineering, Departments of Biomedical Engineering and Electrical and Computer Engineering, 2424 Erwin Road, Suite 302, Durham, North Carolina 27705, United States

J. Med. Imag. 3(3), 035506 (Sep 22, 2016). doi:10.1117/1.JMI.3.3.035506
History: Received April 18, 2016; Accepted September 8, 2016
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Abstract.  The purpose of this study was to compare computed tomography (CT) low-contrast detectability from human readers with observer model-based surrogates of image quality. A phantom with a range of low-contrast signals (five contrasts, three sizes) was imaged on a state-of-the-art CT scanner (Siemens’ force). Images were reconstructed using filtered back projection and advanced modeled iterative reconstruction and were assessed by 11 readers using a two alternative forced choice method. Concurrently, contrast-to-noise ratio (CNR), area-weighted CNR (CNRA), and observer model-based metrics were estimated, including nonprewhitening (NPW) matched filter, NPW with eye filter (NPWE), NPW with internal noise, NPW with an eye filter and internal noise (NPWEi), channelized Hotelling observer (CHO), and CHO with internal noise (CHOi). The correlation coefficients (Pearson and Spearman), linear discriminator error, E, and magnitude of confidence intervals, |CI95%|, were used to determine correlation, proper characterization of the reconstruction algorithms, and model precision, respectively. Pearson (Spearman) correlation was 0.36 (0.33), 0.83 (0.84), 0.84 (0.86), 0.86 (0.88), 0.86 (0.91), 0.88 (0.90), 0.85 (0.89), and 0.87 (0.84), E was 0.25, 0.15, 0.2, 0.25, 0.3, 0.25, 0.4, and 0.45, and |CI95%| was 2.84×103, 5.29×103, 4.91×103, 4.55×103, 2.16×103, 1.24×103, 4.58×102, and 7.95×102 for CNR, CNRA, NPW, NPWE, NPWi, NPWEi, CHO, and CHOi, respectively.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Justin Solomon and Ehsan Samei
"Correlation between human detection accuracy and observer model-based image quality metrics in computed tomography", J. Med. Imag. 3(3), 035506 (Sep 22, 2016). ; http://dx.doi.org/10.1117/1.JMI.3.3.035506


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