This article outlines the statistical developments that have taken place in the use of the EM algorithm in emission and transmission tomography during the past decade or so. We discuss the statistical aspects of the modelling of the projection data for both the emission and transmission cases and define the relevant probability models. This leads to the use of the method of maximum likelihood as a means of estimating the relevant unknown parameters within a given region of a patient's body and to the use of the EM algorithm to compute the reconstruction. Various different types of EM algorithm are discussed, including the SAGE algorithms of Fessler and Hero. The limitations of the EM algorithm, per se, are covered and the need for regulariz...
This article outlines the statistical developments that have taken place in emission tomography duri...
The maximum likelihood (ML) approach to estimating the radioactive distribution in the body cross se...
Statistical methods for approaching image reconstruction and restoration problems have generated muc...
Owing to their complex design and use of live subjects as experimental units, missing or incomplete ...
This paper reviews and compares three maximum likelihood algorithms for transmission tomography. One...
There are many practical problems where the observed data are not drawn directly from the density g ...
The maximum-likelihood (ML) approach in emission tomography provides images with superior noise char...
The maximum-likelihood (ML) approach in emission tomography provides images with superior noise char...
In this paper we formulate a new approach to medical image reconstruction from projections in emissi...
The expectation maximization (EM) algorithm is extensively used for tomographic image reconstruction...
The EM algorithm is not a single algorithm, but a framework for the design of iterative likelihood m...
This paper discusses the EM algorithm. This algorithm is used, for example, to calculate maximum lik...
The Expectation-Maximization (EM) algorithm has become one of the methods of choice for maximum-like...
this paper gives some background about maximum-likelihood estimation in section 2; considers the maj...
In this paper we formulate a new approach to medical image reconstruction from projections in emissi...
This article outlines the statistical developments that have taken place in emission tomography duri...
The maximum likelihood (ML) approach to estimating the radioactive distribution in the body cross se...
Statistical methods for approaching image reconstruction and restoration problems have generated muc...
Owing to their complex design and use of live subjects as experimental units, missing or incomplete ...
This paper reviews and compares three maximum likelihood algorithms for transmission tomography. One...
There are many practical problems where the observed data are not drawn directly from the density g ...
The maximum-likelihood (ML) approach in emission tomography provides images with superior noise char...
The maximum-likelihood (ML) approach in emission tomography provides images with superior noise char...
In this paper we formulate a new approach to medical image reconstruction from projections in emissi...
The expectation maximization (EM) algorithm is extensively used for tomographic image reconstruction...
The EM algorithm is not a single algorithm, but a framework for the design of iterative likelihood m...
This paper discusses the EM algorithm. This algorithm is used, for example, to calculate maximum lik...
The Expectation-Maximization (EM) algorithm has become one of the methods of choice for maximum-like...
this paper gives some background about maximum-likelihood estimation in section 2; considers the maj...
In this paper we formulate a new approach to medical image reconstruction from projections in emissi...
This article outlines the statistical developments that have taken place in emission tomography duri...
The maximum likelihood (ML) approach to estimating the radioactive distribution in the body cross se...
Statistical methods for approaching image reconstruction and restoration problems have generated muc...