Maximum-Likelihood Methods for Processing Signals From Gamma-Ray Detectors

By H. H. Barrett, William C. J. Hunter, Brian W. Miller, Stephen K. Moore, Yi-Chen Chen, Lars R. Furenlid. 2009

166 citations recorded by the source corpus.

In any gamma-ray detector, each event produces electrical signals on one or more circuit elements. From these signals, we may wish to determine the presence of an interaction; whether multiple interactions occurred; the spatial coordinates in two or three dimensions of at least the primary interaction; or the total energy deposited in that interaction. We may also want to compute listmode probabilities for tomographic reconstruction. Maximum-likelihood methods provide a rigorous and in some senses optimal approach to extracting this information, and the associated Fisher information matrix provides a way of quantifying and optimizing the information conveyed by the detector. This paper will review the principles of likelihood methods as applied to gamma-ray detectors and illustrate their power with recent results from the Center for Gamma-ray Imaging.

Subfields: Biomedical Engineering, Radiation, Radiology, Nuclear Medicine and Imaging

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Luca Caucci
2. H. H. Barrett
3. Lars R. Furenlid
4. J. Hesterman
5. Matthew A. Kupinski

In Radiation

1. Luca Caucci
2. Lars R. Furenlid
3. J. Hesterman
4. Matthew A. Kupinski
5. H. H. Barrett

In Radiology, Nuclear Medicine and Imaging

1. Luca Caucci
2. Lars R. Furenlid
3. H. H. Barrett
4. J. Hesterman
5. Matthew A. Kupinski

Citations in the corpus

• Maximum-Likelihood Estimation With a Contracting-Grid Search Algorithm (2010, methodology): “ML estimation methods possess several desirable properties [1], [ 2 ].”