TY - JOUR
T1 - List-mode likelihood
T2 - EM algorithm and image quality estimation demonstrated on 2-D PET
AU - Parra, Lucas
AU - Barrett, Harrison H.
N1 - Funding Information:
Manuscript received September 16, 1996; revised February 27, 1998. The work of H. H. Barrett was supported by the National Cancer Institute under Grant R01 CA52643. The Associate Editor responsible for coordinating the review of this paper and recommending its publication was D. W. Townsend. Asterisk indicates corresponding author. *L. Parra was with Imaging and Visualization, Siemens Corporate Research, Princeton, NJ 08540 USA. He is now with Sarnoff Corporation, CN-5300, Princeton, NJ 08543 USA (e-mail: [email protected]).
PY - 1998
Y1 - 1998
N2 - Using a theory of list-mode maximum-likelihood (ML) source reconstruction presented recently by Barrett et al. [1], this paper formulates a corresponding expectationmaximization (EM) algorithm, as well as a method for estimating noise properties at the ML estimate. List-mode ML is of interest in cases where the dimensionality of the measurement space impedes a binning of the measurement data. It can be advantageous in cases where a better forward model can be obtained by including more measurement coordinates provided by a given detector. Different figures of merit for the detector performance can be computed from the Fisher information matrix (FIM). This paper uses the observed FIM, which requires a single data set, thus, avoiding costly ensemble statistics. The proposed techniques are demonstrated for an idealized two-dimensional (2-D) positron emission tomography (PET) [2-D PET] detector. We compute from simulation data the improved image quality obtained by including the time of flight of the coincident quanta.
AB - Using a theory of list-mode maximum-likelihood (ML) source reconstruction presented recently by Barrett et al. [1], this paper formulates a corresponding expectationmaximization (EM) algorithm, as well as a method for estimating noise properties at the ML estimate. List-mode ML is of interest in cases where the dimensionality of the measurement space impedes a binning of the measurement data. It can be advantageous in cases where a better forward model can be obtained by including more measurement coordinates provided by a given detector. Different figures of merit for the detector performance can be computed from the Fisher information matrix (FIM). This paper uses the observed FIM, which requires a single data set, thus, avoiding costly ensemble statistics. The proposed techniques are demonstrated for an idealized two-dimensional (2-D) positron emission tomography (PET) [2-D PET] detector. We compute from simulation data the improved image quality obtained by including the time of flight of the coincident quanta.
KW - Em algorithm
KW - List-mode data
KW - Maximumlikelihood
KW - Pet reconstruction
KW - Time-of-flight pet
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U2 - 10.1109/42.700734
DO - 10.1109/42.700734
M3 - Article
C2 - 9688154
AN - SCOPUS:0032034223
SN - 0278-0062
VL - 17
SP - 228
EP - 235
JO - IEEE Transactions on Medical Imaging
JF - IEEE Transactions on Medical Imaging
IS - 2
ER -