DocumentCode :
795192
Title :
Propagation of measurement noise through backprojection reconstruction in electrical impedance tomography
Author :
Frangi, Alejandro F. ; Riu, Pere J. ; Rosell, Javier ; Viergever, Max A.
Volume :
21
Issue :
6
fYear :
2002
fDate :
6/1/2002 12:00:00 AM
Firstpage :
566
Lastpage :
578
Abstract :
A framework to analyze the propagation of measurement noise through backprojection reconstruction algorithms in electrical impedance tomography (EIT) is presented. Two measurement noise sources were considered: noise in the current drivers and in the voltage detectors. The influence of the acquisition system architecture (serial/semi-parallel) is also discussed. Three variants of backprojection reconstruction are studied: basic (unweighted), weighted and exponential backprojection. The results of error propagation theory have been compared with those obtained from simulated and experimental data. This comparison shows that the approach provides a good estimate of the reconstruction error variance. It is argued that the reconstruction error in EIT images obtained via backprojection can be approximately modeled as a spatially nonstationary Gaussian distribution. This methodology allows us to develop a spatial characterization of the reconstruction error in EIT images.
Keywords :
Gaussian distribution; electric impedance imaging; image reconstruction; measurement errors; medical image processing; acquisition system architecture; backprojection reconstruction; current drivers; electrical impedance tomography; error propagation theory; medical diagnostic imaging; reconstruction error; reconstruction error characterization; spatial characterization; spatially nonstationary Gaussian distribution; voltage detectors; Algorithm design and analysis; Current measurement; Detectors; Electric variables measurement; Image reconstruction; Impedance measurement; Noise measurement; Reconstruction algorithms; Tomography; Voltage; Algorithms; Artifacts; Computer Simulation; Electric Impedance; Humans; Image Enhancement; Models, Biological; Models, Statistical; Normal Distribution; Phantoms, Imaging; Sensitivity and Specificity; Stochastic Processes; Thorax; Tomography;
fLanguage :
English
Journal_Title :
Medical Imaging, IEEE Transactions on
Publisher :
ieee
ISSN :
0278-0062
Type :
jour
DOI :
10.1109/TMI.2002.800612
Filename :
1021921
Link To Document :
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