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|a 10.1109/TIP.2002.806253
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|a eng
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|a Feng, Haihua
|e verfasserin
|4 aut
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| 245 |
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|a A curve evolution approach to object-based tomographic reconstruction
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|c 2003
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|a Text
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|a ƒaComputermedien
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|a ƒa Online-Ressource
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|a Date Completed 20.05.2010
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|a Date Revised 01.02.2008
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|a published: Print
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|a Citation Status PubMed-not-MEDLINE
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|a In this paper, we develop a new approach to tomographic reconstruction problems based on geometric curve evolution techniques. We use a small set of texture coefficients to represent the object and background inhomogeneities and a contour to represent the boundary of multiple connected or unconnected objects. Instead of reconstructing pixel values on a fixed rectangular grid, we then find a reconstruction by jointly estimating these unknown contours and texture coefficients of the object and background. By designing a new "tomographic flow", the resulting problem is recast into a curve evolution problem and an efficient algorithm based on level set techniques is developed. The performance of the curve evolution method is demonstrated using examples with noisy limited-view Radon transformed data and noisy ground-penetrating radar data. The reconstruction results and computational cost are compared with those of conventional, pixel-based regularization methods. The results indicate that the curve evolution methods achieve improved shape reconstruction and have potential computation and memory advantages over conventional regularized inversion methods
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|a Journal Article
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|a Karl, William Clem
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Castañon, David A
|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 12(2003), 1 vom: 28., Seite 44-57
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|x 1941-0042
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|g year:2003
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|u http://dx.doi.org/10.1109/TIP.2002.806253
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