
Proceedings Paper
Estimating ROI activity concentration with photon-processing and photon-counting SPECT imaging systemsFormat | Member Price | Non-Member Price |
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Paper Abstract
Recently a new class of imaging systems, referred to as photon-processing (PP) systems, are being developed
that uses real-time maximum-likelihood (ML) methods to estimate multiple attributes per detected photon and
store these attributes in a list format. PP systems could have a number of potential advantages compared
to systems that bin photons based on attributes such as energy, projection angle, and position, referred to as
photon-counting (PC) systems. For example, PP systems do not suffer from binning-related information loss and
provide the potential to extract information from attributes such as energy deposited by the detected photon.
To quantify the effects of this advantage on task performance, objective evaluation studies are required. We
performed this study in the context of quantitative 2-dimensional single-photon emission computed tomography
(SPECT) imaging with the end task of estimating the mean activity concentration within a region of interest
(ROI). We first theoretically outline the effect of null space on estimating the mean activity concentration, and
argue that due to this effect, PP systems could have better estimation performance compared to PC systems with
noise-free data. To evaluate the performance of PP and PC systems with noisy data, we developed a singular
value decomposition (SVD)-based analytic method to estimate the activity concentration from PP systems. Using
simulations, we studied the accuracy and precision of this technique in estimating the activity concentration.
We used this framework to objectively compare PP and PC systems on the activity concentration estimation
task. We investigated the effects of varying the size of the ROI and varying the number of bins for the attribute
corresponding to the angular orientation of the detector in a continuously rotating SPECT system. The results
indicate that in several cases, PP systems offer improved estimation performance compared to PC systems.
Paper Details
Date Published: 13 April 2015
PDF: 11 pages
Proc. SPIE 9412, Medical Imaging 2015: Physics of Medical Imaging, 94120R (13 April 2015); doi: 10.1117/12.2082278
Published in SPIE Proceedings Vol. 9412:
Medical Imaging 2015: Physics of Medical Imaging
Christoph Hoeschen; Despina Kontos, Editor(s)
PDF: 11 pages
Proc. SPIE 9412, Medical Imaging 2015: Physics of Medical Imaging, 94120R (13 April 2015); doi: 10.1117/12.2082278
Show Author Affiliations
Abhinav K. Jha, Johns Hopkins Univ. (United States)
Eric C. Frey, Johns Hopkins Univ. (United States)
Published in SPIE Proceedings Vol. 9412:
Medical Imaging 2015: Physics of Medical Imaging
Christoph Hoeschen; Despina Kontos, Editor(s)
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