DocumentCode :
951213
Title :
Improving the accuracy of volumetric segmentation using pre-processing boundary detection and image reconstruction
Author :
Archibald, Rick ; Hu, Jiuxiang ; Gelb, Anne ; Farin, Gerald
Author_Institution :
Center for Syst. Sci. & Eng. Res., Arizona State Univ., Tempe, AZ, USA
Volume :
13
Issue :
4
fYear :
2004
fDate :
4/1/2004 12:00:00 AM
Firstpage :
459
Lastpage :
466
Abstract :
The concentration edge -detection and Gegenbauer image-reconstruction methods were previously shown to improve the quality of segmentation in magnetic resonance imaging. In this study, these methods are utilized as a pre-processing step to the Weibull E-SD field segmentation. It is demonstrated that the combination of the concentration edge detection and Gegenbauer reconstruction method improves the accuracy of segmentation for the simulated test data and real magnetic resonance images used in this study.
Keywords :
Weibull distribution; edge detection; image reconstruction; image segmentation; magnetic resonance imaging; Gegenbauer image reconstruction; Weibull E-SD field segmentation; Weibull distribution; concentration edge detection; expectancy-standard deviation; magnetic resonance imaging; preprocessing boundary detection; volumetric segmentation; Image edge detection; Image reconstruction; Image segmentation; Magnetic field measurement; Magnetic resonance; Magnetic resonance imaging; Multidimensional systems; Reconstruction algorithms; Systems engineering and theory; Testing; Algorithms; Animals; Brain; Computer Simulation; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Information Storage and Retrieval; Magnetic Resonance Imaging; Mice; Pattern Recognition, Automated; Quality Control; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/TIP.2003.819862
Filename :
1284382
Link To Document :
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