Computing Reconstruction Kernels for Circular 3-D Cone Beam Tomography

In this paper, we present techniques for deriving inversion algorithms in 3-D computer tomography. To this end, we introduce the mathematical model and apply a general strategy, the so-called approximate inverse, for deriving both exact and numerical inversion formulas. Using further approximations,...

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Bibliographic Details
Published in:IEEE transactions on medical imaging 2008-07, Vol.27 (7), p.880-886
Main Authors: Louis, A.K., Weber, T., Theis, D.
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Computed tomography
Computer Simulation
Cone-beam computed tomography (CT)
Damping
Fourier Analysis
Geometry
Hilbert space
Humans
Image reconstruction
Imaging, Three-Dimensional - methods
Inverse problems
Kernel
Mathematical model
Mathematics
Models, Theoretical
mollifier
Numerical Analysis, Computer-Assisted
Phantoms, Imaging
reconstruction kernel
Software
Tomography, X-Ray Computed - methods
X-ray imaging
X-ray tomography
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Summary:In this paper, we present techniques for deriving inversion algorithms in 3-D computer tomography. To this end, we introduce the mathematical model and apply a general strategy, the so-called approximate inverse, for deriving both exact and numerical inversion formulas. Using further approximations, we derive a 2-D shift-invariant filter for circular-orbit cone-beam imaging. Results from real data are presented.
ISSN:0278-0062
1558-254X
DOI:10.1109/TMI.2008.922188