Paper
21 March 2007 Evaluation of hardware in a small-animal SPECT system using reconstructed images
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Abstract
Evaluation of imaging hardware represents a vital component of system design. In small-animal SPECT imaging, this evaluation has become increasingly diffcult with the emergence of multi-pinhole apertures and adaptive, or patient-specific, imaging. This paper will describe two methods for hardware evaluation using reconstructed images. The first method is a rapid technique incorporating a system-specific non-linear, three-dimensional point response. This point response is easily computed and offers qualitative insight into an aperture's resolution and artifact characteristics. The second method is an objective assessment of signal detection in lumpy backgrounds using the channelized Hotelling observer (CHO) with 3D Laguerre-Gauss and difference-of-Gaussian channels to calculate area under the receiver-operating characteristic curve (AUC). Previous work presented at this meeting described a unique, small-animal SPECT system (M3R) capable of operating under a myriad of hardware configurations and ideally suited for image quality studies. Measured system matrices were collected for several hardware configurations of M3R. The data used to implement these two methods was then generated by taking simulated objects through the measured system matrices. The results of these two methods comprise a combination of qualitative and quantitative analysis that is well-suited for hardware assessment.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jacob Y. Hesterman, Matthew A. Kupinski, Eric Clarkson, Donald W. Wilson, and Harrison H. Barrett "Evaluation of hardware in a small-animal SPECT system using reconstructed images", Proc. SPIE 6515, Medical Imaging 2007: Image Perception, Observer Performance, and Technology Assessment, 65151G (21 March 2007); https://doi.org/10.1117/12.709730
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Cited by 6 scholarly publications.
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KEYWORDS
Imaging systems

Single photon emission computed tomography

Objectives

Signal detection

Image quality

Matrices

Cameras

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