TY - GEN
T1 - Optimizability of loglikelihoods for the estimation of detector efficiencies and singles rates in PET
AU - Jacobson, Matthew W.
AU - Thielemans, Kris
PY - 2008/12/1
Y1 - 2008/12/1
N2 - In various prior work, Poisson models have been proposed for normalization scan and delayed coincidence measurements in PET systems. In these models, the mean measured counts are given by pair-wise products of a set of unknown detector efficiency or singles rate parameters. Additionally, several kinds of iterative algorithms have been proposed for solving the associated maximum likelihood estimation problem, and have exhibited strong empirical performance. To our knowledge, however, no analysis has been given proving that these algorithms actually converge, but only that convergence, should it hypothetically occur, would have to be to a stationary point of the loglikelihood. One of the main obstacles to a complete convergence analysis is showing that the loglikelihood actually possesses a finite maximizer. As we will show, there are cases where the loglikelihood function for these applications can approach its maximum value only by letting the unknown parameters tend asymptotically to infinity. In such cases, convergent behavior is not possible with any algorithm because there is nothing to converge to. In this article, we derive sufficient conditions - for cylindrical PET system geometries - guaranteeing not only that a unique and finite maximizer exists, but also that the loglikelihood maximization is equivalent to minimizing a strictly convex function. The latter obviates many questions of convergent algorithm design, since virtually any minimization algorithm with standard monotonicity and stationary properties will convergently minimize a strictly convex function when the minimizer exists. The conditions that we derive are, oreover, readily verifiable by preanalysis of the projection measurements and show that failure of a solution to exist is a very rare event, xcept for unrealistically low count scans or for systems with unrealistically dense patterns of malfunctioning detectors.
AB - In various prior work, Poisson models have been proposed for normalization scan and delayed coincidence measurements in PET systems. In these models, the mean measured counts are given by pair-wise products of a set of unknown detector efficiency or singles rate parameters. Additionally, several kinds of iterative algorithms have been proposed for solving the associated maximum likelihood estimation problem, and have exhibited strong empirical performance. To our knowledge, however, no analysis has been given proving that these algorithms actually converge, but only that convergence, should it hypothetically occur, would have to be to a stationary point of the loglikelihood. One of the main obstacles to a complete convergence analysis is showing that the loglikelihood actually possesses a finite maximizer. As we will show, there are cases where the loglikelihood function for these applications can approach its maximum value only by letting the unknown parameters tend asymptotically to infinity. In such cases, convergent behavior is not possible with any algorithm because there is nothing to converge to. In this article, we derive sufficient conditions - for cylindrical PET system geometries - guaranteeing not only that a unique and finite maximizer exists, but also that the loglikelihood maximization is equivalent to minimizing a strictly convex function. The latter obviates many questions of convergent algorithm design, since virtually any minimization algorithm with standard monotonicity and stationary properties will convergently minimize a strictly convex function when the minimizer exists. The conditions that we derive are, oreover, readily verifiable by preanalysis of the projection measurements and show that failure of a solution to exist is a very rare event, xcept for unrealistically low count scans or for systems with unrealistically dense patterns of malfunctioning detectors.
KW - Detector efficiencies
KW - Maximum likelihood
KW - PET
KW - Singles
UR - http://www.scopus.com/inward/record.url?scp=67649194616&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=67649194616&partnerID=8YFLogxK
U2 - 10.1109/NSSMIC.2008.4774352
DO - 10.1109/NSSMIC.2008.4774352
M3 - Conference contribution
AN - SCOPUS:67649194616
SN - 9781424427154
T3 - IEEE Nuclear Science Symposium Conference Record
SP - 4580
EP - 4586
BT - 2008 IEEE Nuclear Science Symposium Conference Record, NSS/MIC 2008
T2 - 2008 IEEE Nuclear Science Symposium Conference Record, NSS/MIC 2008
Y2 - 19 October 2008 through 25 October 2008
ER -