Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
The mathematics of computerized tomography
The mathematics of computerized tomography
Principles of computerized tomographic imaging
Principles of computerized tomographic imaging
Discrete tomography by convex-concave regularization and D.C. programming
Discrete Applied Mathematics - Special issue: IWCIA 2003 - Ninth international workshop on combinatorial image analysis
Binary tomography by iterating linear programs from noisy projections
IWCIA'04 Proceedings of the 10th international conference on Combinatorial Image Analysis
Generic iterative subset algorithms for discrete tomography
Discrete Applied Mathematics
Discrete tomography reconstruction based on the multi-well potential
IWCIA'11 Proceedings of the 14th international conference on Combinatorial image analysis
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Tomography deals with the reconstruction of images from their projections In this paper we focus on tomographic reconstruction of binary images (i.e., black-and-white) that do not have an intrinsic lattice structure from a small number of projections We describe how the reconstruction problem from only two projections can be formulated as a network flow problem in a graph, which can be solved efficiently When only two projections are used, the reconstruction problem is severely underdetermined and many solutions may exist To find a reconstruction that resembles the original image, more projections must be used We propose an iterative algorithm to solve the reconstruction problem from more than two projections In every iteration a network flow problem is solved, corresponding to two of the available projections Different pairs of projection angles are used for consecutive iterations Our algorithm is capable of computing high quality reconstructions from very few projections We evaluate its performance on simulated projection data and compare it to other reconstruction algorithms.