1,322 research outputs found
Erratum
The influence of temperature during the development of conidia on the germination of Uncinula necatorVitis 34(1), 63-64 (1995
Regularized Emission Image Reconstruction Using Imperfect Side Information
A spatially variant penalized-likelihood method for tomographic image reconstruction based on a weighted Gibbs penalty was investigated. The penalty weights are determined from structural side information, such as the locations of anatomical boundaries in high-resolution magnetic resonance images. Such side information will be imperfect in practice, and a simple simulation demonstrated the importance of accounting for the errors in boundary locations. Methods are discussed for prescribing the penalty weights when the side information is noisy. Simulation results suggest that even imperfect side information is useful for guiding spatially variant regularization.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85869/1/Fessler110.pd
Robust Maximum- Likelihood Position Estimation in Scintillation Cameras
The classical maximum-likelihood (ML) estimator for the
position of a scintillation event in a gamma camera, as derived
by Gray and Macovski in 1976, requires exact knowledge
of the light-spread function (LSF) of each photomultiplier
tube. In practice, one must determine each LSF from
noisy measurements corrupted by Poisson noise, quantization
error, and electronic noise and bias. Since the ML
position estimator involves derivatives of each LSF, even
small measurement errors can result in degraded estimator
performance. In this paper we derive a robust ML position
estimator that accounts for the statistical uncertainty
in LSF measurements. The form of the robust estimator
diminishes contributions from the tails of the LSF, where
the relative measurement errors are the largest.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85879/1/Fessler117.pd
Fast Parallelizable Algorithms for Transmission Image Reconstruction
Presents a new class of algorithm for penalized-likelihood reconstruction of attenuation maps from low-count transmission scans. The authors derive the algorithms by applying to the transmission log-likelihood a variation of the convexity technique developed by De Pierro for the emission case. The new algorithms overcome several limitations associated with previous algorithms. (1) Fewer exponentiations are required than in the transmission EM algorithm or in coordinate-ascent algorithms. (2) The algorithms intrinsically accommodate nonnegativity constraints, unlike many gradient-based methods. (3) The algorithms are easily parallelizable, unlike coordinate-ascent algorithms and perhaps line-search algorithms. The authors show that the algorithms converge faster than several alternatives, even on conventional workstations. They give examples from low-count PET transmission scans and from truncated fan-beam SPECT transmission scans.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86006/1/Fessler136.pd
Maximum-Likelihood Dual-Energy TomographicImage Reconstruction
Dual-energy (DE) X-ray computed tomography (CT) has shown promise for material characterization and for providing
quantitatively accurate CT values in a variety of applications. However, DE-CT has not been used routinely in medicine to
date, primarily due to dose considerations. Most methods for DE-CT have used the filtered backprojection method for image
reconstruction, leading to suboptimal noise/dose properties. This paper describes a statistical (maximum-likelihood)
method for dual-energy X-ray CT that accommodates a wide variety of potential system configurations and measurement
noise models. Regularized methods (such as penalized-likelihood or Bayesian estimation) are straightforward extensions.
One version of the algorithm monotonically decreases the negative log-likelihood cost function each iteration. An
ordered-subsets variation of the algorithm provides a fast and practical version.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85934/1/Fessler172.pd
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