Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
An efficient implementation of a scaling minimum-cost flow algorithm
Journal of Algorithms
On the computational complexity of reconstructing lattice sets from their x-rays
Discrete Mathematics
Approximating Binary Images from Discrete X-Rays
SIAM Journal on Optimization
SIAM Journal on Discrete Mathematics
Advances in Discrete Tomography and Its Applications (Applied and Numerical Harmonic Analysis)
Advances in Discrete Tomography and Its Applications (Applied and Numerical Harmonic Analysis)
Binary matrices under the microscope: A tomographical problem
Theoretical Computer Science
A Network Flow Algorithm for Reconstructing Binary Images from Discrete X-rays
Journal of Mathematical Imaging and Vision
A network flow algorithm for binary image reconstruction from few projections
DGCI'06 Proceedings of the 13th international conference on Discrete Geometry for Computer Imagery
A benchmark evaluation of large-scale optimization approaches to binary tomography
DGCI'06 Proceedings of the 13th international conference on Discrete Geometry for Computer Imagery
IWCIA'06 Proceedings of the 11th international conference on Combinatorial Image Analysis
Error bounds on the reconstruction of binary images from low resolution scans
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part I
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Discrete tomography deals with the reconstruction of images from their projections where the images are assumed to contain only a small number of grey values. In particular, there is a strong focus on the reconstruction of binary images (binary tomography). A variety of binary tomography problems have been considered in the literature, each using different projection models or additional constraints. In this paper, we propose a generic iterative reconstruction algorithm that can be used for many different binary reconstruction problems. In every iteration, a subproblem is solved based on at most two of the available projections. Each of the subproblems can be solved efficiently using network flow methods. We report experimental results for various reconstruction problems. Our results demonstrate that the algorithm is capable of reconstructing complex objects from a small number of projections.