ADART: An Adaptive Algebraic Reconstruction Algorithm for Discrete Tomography

In this paper we suggest an algorithm based on the Discrete Algebraic Reconstruction Technique (DART) which is capable of computing high quality reconstructions from substantially fewer projections than required for conventional continuous tomography. Adaptive DART (ADART) goes a step further than D...

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Bibliographic Details
Published in:IEEE transactions on image processing 2011-08, Vol.20 (8), p.2146-2152
Main Authors: Maestre-Deusto, F. J., Scavello, G., Pizarro, J., Galindo, P. L.
Format: Article
Language:English
Subjects:
ADART
Algebra
algebraic reconstruction technique
Algorithms
Applied sciences
Borders
DART
discrete tomography
Equations
Exact sciences and technology
Head - anatomy & histology
Humans
Image processing
Image Processing, Computer-Assisted - methods
Image reconstruction
Information, signal and communications theory
Linear systems
Models, Theoretical
Noise
Phantoms, Imaging
Pixel
Pixels
Reconstruction
Reconstruction algorithms
Reduction
Signal processing
Studies
Telecommunications and information theory
Tomography
Tomography - methods
Transforms
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Summary:In this paper we suggest an algorithm based on the Discrete Algebraic Reconstruction Technique (DART) which is capable of computing high quality reconstructions from substantially fewer projections than required for conventional continuous tomography. Adaptive DART (ADART) goes a step further than DART on the reduction of the number of unknowns of the associated linear system achieving a significant reduction in the pixel error rate of reconstructed objects. The proposed methodology automatically adapts the border definition criterion at each iteration, resulting in a reduction of the number of pixels belonging to the border, and consequently of the number of unknowns in the general algebraic reconstruction linear system to be solved, being this reduction specially important at the final stage of the iterative process. Experimental results show that reconstruction errors are considerably reduced using ADART when compared to original DART, both in clean and noisy environments.
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2011.2114894