An evolutionary algorithm for discrete tomography
Kees Joost Batenburg
- Vol. 151, Iss: 1, pp 36-54
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TLDR
This paper presents an evolutionary algorithm for finding the reconstruction which maximises an evaluation function, representing the ''quality'' of the reconstruction, and shows that the algorithm can be successfully applied to a wide range of evaluation functions.Abstract:
One of the main problems in discrete tomography is the reconstruction of binary matrices from their projections in a small number of directions In this paper we consider a new algorithmic approach for reconstructing binary matrices from only two projections This problem is usually underdetermined and the number of solutions can be very large We present an evolutionary algorithm for finding the reconstruction which maximises an evaluation function, representing the ''quality'' of the reconstruction, and show that the algorithm can be successfully applied to a wide range of evaluation functions We discuss the necessity of a problem-specific representation and tailored search-operators for obtaining satisfactory results Our new search-operators can also be used in other discrete tomography algorithmsread more
Citations
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Approximating bicolored images from discrete projections
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Tomographic reconstruction of isotropic materials using genetic algorithms with ultrasound time-of-flight projection data
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A Novel Convex Relaxation for Non-Binary Discrete Tomography
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RESEARCH ARTICLE Discrete Tomographic Reconstruction via Adaptive Weighting of Gradient Descents
TL;DR: In this article, an energy minimization approach is proposed for multivalued discrete tomography (MDDT) reconstruction, where the reconstruction is formulated as a non-destructive testing problem.
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