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231223s2009 xx |||||o 00| ||eng c |
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|a 10.1109/TIP.2009.2017139
|2 doi
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|a DE-627
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|e rakwb
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|a eng
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| 100 |
1 |
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|a Xu, Jingyan
|e verfasserin
|4 aut
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| 245 |
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|a Electronic noise modeling in statistical iterative reconstruction
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|c 2009
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
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|2 rdacarrier
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| 500 |
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|a Date Completed 27.08.2009
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|a Date Revised 20.10.2021
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a We consider electronic noise modeling in tomographic image reconstruction when the measured signal is the sum of a Gaussian distributed electronic noise component and another random variable whose log-likelihood function satisfies a certain linearity condition. Examples of such likelihood functions include the Poisson distribution and an exponential dispersion (ED) model that can approximate the signal statistics in integration mode X-ray detectors. We formulate the image reconstruction problem as a maximum-likelihood estimation problem. Using an expectation-maximization approach, we demonstrate that a reconstruction algorithm can be obtained following a simple substitution rule from the one previously derived without electronic noise considerations. To illustrate the applicability of the substitution rule, we present examples of a fully iterative reconstruction algorithm and a sinogram smoothing algorithm both in transmission CT reconstruction when the measured signal contains additive electronic noise. Our simulation studies show the potential usefulness of accurate electronic noise modeling in low-dose CT applications
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|a Journal Article
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| 650 |
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|a Research Support, Non-U.S. Gov't
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| 700 |
1 |
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|a Tsui, Benjamin M W
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 18(2009), 6 vom: 08. Juni, Seite 1228-38
|w (DE-627)NLM09821456X
|x 1941-0042
|7 nnns
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| 773 |
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|g volume:18
|g year:2009
|g number:6
|g day:08
|g month:06
|g pages:1228-38
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|u http://dx.doi.org/10.1109/TIP.2009.2017139
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