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Proceedings Paper

A resampling comparison of CHO's detectability index bias and uncertainty
Author(s): Francesc Massanes; Alexandre Ba; François Bochud; Jovan G. Brankov
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Paper Abstract

Model observers have gained popularity as a surrogate approach for image quality assessment, they are often used for the optimization of the reconstruction algorithm. The most widespread model observer is the channelized Hotelling observer (CHO) that allows measuring the image quality by calculating the detectability index (or associated area under receiver operating characteristic curve). In this work we have chosen to explore different resampling methods used to estimate the CHO performance and uncertainty. In this paper, using data from the inter-laboratory comparison of the computation of CHO model observer study, we established a simulation framework to fully evaluate different resampling methods, namely, leave-one out and bootstrapping with replacement to estimate the CHO’s detectability index bias and uncertainty. For this particular study, we focus our experiments on datasets with a few data samples, 200 normal and 200 abnormal images.

Paper Details

Date Published: 12 March 2018
PDF: 7 pages
Proc. SPIE 10577, Medical Imaging 2018: Image Perception, Observer Performance, and Technology Assessment, 105770V (12 March 2018); doi: 10.1117/12.2297689
Show Author Affiliations
Francesc Massanes, Illinois Institute of Technology (United States)
Alexandre Ba, Institut Univ. de Radiophysique Appliquée (Switzerland)
François Bochud, Institut Univ. de Radiophysique Appliquée (Switzerland)
Jovan G. Brankov, Illinois Institute of Technology (United States)


Published in SPIE Proceedings Vol. 10577:
Medical Imaging 2018: Image Perception, Observer Performance, and Technology Assessment
Robert M. Nishikawa; Frank W. Samuelson, Editor(s)

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