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Proceedings Paper

Scanning model observers to predict human performance in LROC studies of SPECT reconstruction using anatomical priors
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Paper Abstract

We use scanning model observers to predict human performance in lesion search/detection study. The observer's task is to locate gallium-avid tumors in simulated SPECT images of a digital phantom. The goal of our model is to predict the optimal prior strength β for human observers of smoothing priors incorporated into the reconstruction algorithm. These priors use varying amounts of anatomical knowledge. We present results from a scanning channelized non-prewhitening matched filter, and compare them with results from a human-observer study. Including a step to mimic the greyscale perceptual-linearization used during the human-observer study improves the accuracy of the model. However we find that for lesions close to an organ boundary even the improved model does not accurately predict human performance.

Paper Details

Date Published: 12 March 2009
PDF: 7 pages
Proc. SPIE 7263, Medical Imaging 2009: Image Perception, Observer Performance, and Technology Assessment, 72631T (12 March 2009); doi: 10.1117/12.813774
Show Author Affiliations
Andre Lehovich, Univ. of Massachusetts Medical School (United States)
Howard C. Gifford, Univ. of Massachusetts Medical School (United States)
Michael A. King, Univ. of Massachusetts Medical School (United States)


Published in SPIE Proceedings Vol. 7263:
Medical Imaging 2009: Image Perception, Observer Performance, and Technology Assessment
Berkman Sahiner; David J. Manning, Editor(s)

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