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Proceedings Paper

Comparison of human- and model-observer LROC studies
Author(s): Howard C. Gifford; P. Hendrik Pretorius; Michael A. King
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Paper Abstract

We have investigated whether extensions of linear model observers can predict human performance in a localization ROC (LROC) study. The specific task was detection of gallium-avid tumors in SPECT images of a mathematical phantom, and the study was intended to quantify the effect of improved detector energy resolution on scatter-corrected images. The basis for our model observers is the latent perception measurement postulated for the LROC model. This measurement is obtained by cross-correlating the image with a kernel, and the LROC rating and localization data are the max and argmax, respectively, of this measurement made at all relevant search locations. The particular model observers tested were the nonprewhitening (NPW), channelized NPW (CNPW), and channelized Hotelling (CH) observers. Specification of the observer's search region was also part of the task definition, and several variations were considered that could approximate the training of human observers. The best agreement with the human observers was found with the CNPW observer, suggesting that the ability of human observers to prewhiten images may be degraded when the detection task requires signal localization.

Paper Details

Date Published: 22 May 2003
PDF: 11 pages
Proc. SPIE 5034, Medical Imaging 2003: Image Perception, Observer Performance, and Technology Assessment, (22 May 2003); doi: 10.1117/12.480341
Show Author Affiliations
Howard C. Gifford, Univ. of Massachusetts Medical School (United States)
P. Hendrik Pretorius, Univ. of Massachusetts Medical School (United States)
Michael A. King, Univ. of Massachusetts Medical School (United States)


Published in SPIE Proceedings Vol. 5034:
Medical Imaging 2003: Image Perception, Observer Performance, and Technology Assessment
Dev P. Chakraborty; Elizabeth A. Krupinski, Editor(s)

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