@article {2356,
	title = {Discrete tomographic reconstruction via adaptive weighting of gradient descents},
	journal = {Computer Methods in Biomechanics and Biomedical Engineering: Imaging \& Visualization},
	volume = {3},
	year = {2015},
	month = {Feb 2014},
	pages = {101-109},
	publisher = {Taylor\&Francis},
	type = {Journal article},
	chapter = {101},
	abstract = {<p>Discrete tomography (DT) is a set of tools for reconstructing the inner structure of objects consisting of only few different homogeneous materials. We propose a new method for multivalued DT, which performs the reconstruction as an energy minimisation task. For this algorithm, we define an energy function that can mathematically formulate the reconstruction task, and design a novel optimisation process for approximating the minima of this energy function. We validate the algorithm by comparing its performance with other cutting-edge reconstruction algorithms from the literature. We show that our method can compete with the currently used reconstruction techniques and under certain circumstances (e.g. with a low number of projections, or when the projection data are affected by random noise) it can even outperform them.</p>},
	doi = {DOI:     10.1080/21681163.2013.853624},
	author = {L{\'a}szl{\'o} G{\'a}bor Varga and P{\'e}ter Bal{\'a}zs and Antal Nagy}
}
