In emission tomography maximum likelihood expectation maximization reconstruction technique has replaced the analytical approaches in several applications. The most important drawback of this iterative method is its linear rate of convergence and the corresponding computational burden. Therefore, simplifications are usually required in the Monte Carlo simulation of the back projection step. In order to overcome these problems, a reconstruction code has been developed with graphical processing unit based Monte Carlo engine which enabled full physical modelling in the back projection
Maximizing some form of Poisson likelihood (either with or without penalization) is central to image...
Stochastic methods based on Maximum Likelihood Estimation (MLE) provide accurate tomographic reconst...
This research investigates the use of Markov random fields for Bayesian reconstruction algorithms to...
Background In emission tomography maximum likelihood expectation maximization reconstruction techniq...
In this paper we formulate a new approach to medical image reconstruction from projections in emissi...
In this paper we formulate a new approach to medical image reconstruction from projections in emissi...
Statistical iterative reconstruction with Monte Carlo system modeling is an effective method in impr...
The expectation maximization (EM) algorithm is extensively used for tomographic image reconstruction...
The maximum-likelihood (ML) approach in emission tomography provides images with superior noise char...
A positron emission tomography (PET) scan does not measure an image directly. Instead, a PET scan me...
Expectation Maximization and Filtered Back Projection are two different techniques for Tomographic r...
Images of the inside of the human body can be obtained non-invasively using tomographic acquisition ...
The maximum-likelihood (ML) approach in emission tomography provides images with superior noise char...
[[abstract]]©2002 MC NTHU - Quantitative positron emission tomography (PET) using statistical techni...
The authors show that the conditional entropy maximisation algorithm is a generalised version of the...
Maximizing some form of Poisson likelihood (either with or without penalization) is central to image...
Stochastic methods based on Maximum Likelihood Estimation (MLE) provide accurate tomographic reconst...
This research investigates the use of Markov random fields for Bayesian reconstruction algorithms to...
Background In emission tomography maximum likelihood expectation maximization reconstruction techniq...
In this paper we formulate a new approach to medical image reconstruction from projections in emissi...
In this paper we formulate a new approach to medical image reconstruction from projections in emissi...
Statistical iterative reconstruction with Monte Carlo system modeling is an effective method in impr...
The expectation maximization (EM) algorithm is extensively used for tomographic image reconstruction...
The maximum-likelihood (ML) approach in emission tomography provides images with superior noise char...
A positron emission tomography (PET) scan does not measure an image directly. Instead, a PET scan me...
Expectation Maximization and Filtered Back Projection are two different techniques for Tomographic r...
Images of the inside of the human body can be obtained non-invasively using tomographic acquisition ...
The maximum-likelihood (ML) approach in emission tomography provides images with superior noise char...
[[abstract]]©2002 MC NTHU - Quantitative positron emission tomography (PET) using statistical techni...
The authors show that the conditional entropy maximisation algorithm is a generalised version of the...
Maximizing some form of Poisson likelihood (either with or without penalization) is central to image...
Stochastic methods based on Maximum Likelihood Estimation (MLE) provide accurate tomographic reconst...
This research investigates the use of Markov random fields for Bayesian reconstruction algorithms to...