TY - GEN
T1 - Estimating ROI activity concentration with photon-processing and photon-counting SPECT imaging systems
AU - Jha, Abhinav K.
AU - Frey, Eric C.
N1 - Publisher Copyright:
© 2015 SPIE.
PY - 2015
Y1 - 2015
N2 - 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.
AB - 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.
KW - Analytic ROI activity estimation
KW - LM acquisition
KW - Null functions
KW - Photon-processing systems
KW - SPECT
KW - Singular-value decom-position
UR - http://www.scopus.com/inward/record.url?scp=84943303301&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84943303301&partnerID=8YFLogxK
U2 - 10.1117/12.2082278
DO - 10.1117/12.2082278
M3 - Conference contribution
C2 - 26430291
AN - SCOPUS:84943303301
T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE
BT - Medical Imaging 2015
A2 - Hoeschen, Christoph
A2 - Kontos, Despina
A2 - Hoeschen, Christoph
PB - SPIE
T2 - Medical Imaging 2015: Physics of Medical Imaging
Y2 - 22 February 2015 through 25 February 2015
ER -