A Multi-channel DART Algorithm
Math\'e Zeegers, Felix Lucka, Kees Joost Batenburg

TL;DR
The paper introduces Multi-Channel DART (MC-DART), an advanced tomography algorithm that leverages multi-channel data to improve reconstruction accuracy for objects with multiple materials, outperforming traditional single-channel DART.
Contribution
The paper presents MC-DART, a novel multi-channel extension of DART that effectively utilizes multi-channel tomographic data for enhanced reconstruction accuracy.
Findings
MC-DART outperforms single-channel DART in simulation experiments.
Multi-channel data improves reconstruction accuracy for objects with multiple materials.
MC-DART effectively exploits additional information from multiple channels.
Abstract
Tomography deals with the reconstruction of objects from their projections, acquired along a range of angles. Discrete tomography is concerned with objects that consist of a small number of materials, which makes it possible to compute accurate reconstructions from highly limited projection data. For cases where the allowed intensity values in the reconstruction are known a priori, the discrete algebraic reconstruction technique (DART) has shown to yield accurate reconstructions from few projections. However, a key limitation is that the benefit of DART diminishes as the number of different materials increases. Many tomographic imaging techniques can simultaneously record tomographic data at multiple channels, each corresponding to a different weighting of the materials in the object. Whenever projection data from more than one channel is available, this additional information can…
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