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Proceedings Paper

SPECT image system optimization using ideal observer for detection and localization
Author(s): Lili Zhou; Gene Gindi
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Paper Abstract

We consider the problem of optimizing collimator characteristics for a simple emission tomographic imaging system. We use the performance of two different ideal observers to carry out the optimization. The first ideal observer applies to signal detection when signal location is unknown and background is variable, and the second ideal observer (one proposed previously by our group) to the more realistic task of signal detection and localization with signal location unknown and background variable. The two observers operate on sinogram data to deliver scalar figures of merit AROC and ALROC, respectively. We considered three different collimators that span a range of efficiency-resolution tradeoffs. Our central question is this: For optimizing the collimator in an emission tomographic system, does adding a localization requirement to a detection task yield an efficiency-resolution tradeoff that differs from that for the detection-only task? Our simulations with a simple SPECT imaging system show that as the localization requirement becomes more stringent, the optimal collimator shifts from a low-resolution, high efficiency version toward higher resolution, lower efficiency version. We had previously observed such behavior for a planar pinhole imaging system. In our simulations, we used a simplified model of tomographic imaging and a simple model for object background variability. This allowed us to avoid the severe computational complexity associated with ideal-observer performance calculations. Thus the more realistic task (i.e. localization included) resulted for this case in a different optimal collimator.

Paper Details

Date Published: 6 March 2008
PDF: 8 pages
Proc. SPIE 6917, Medical Imaging 2008: Image Perception, Observer Performance, and Technology Assessment, 69171D (6 March 2008); doi: 10.1117/12.770676
Show Author Affiliations
Lili Zhou, Stony Brook Univ. (United States)
Gene Gindi, Stony Brook Univ. (United States)

Published in SPIE Proceedings Vol. 6917:
Medical Imaging 2008: Image Perception, Observer Performance, and Technology Assessment
Berkman Sahiner; David J. Manning, Editor(s)

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