Regularized graph cuts based discrete tomography reconstruction methods

Marina Marčeta () and Tibor Lukić ()
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Marina Marčeta: University of Novi Sad
Tibor Lukić: University of Novi Sad

Journal of Combinatorial Optimization, 2022, vol. 44, issue 4, No 10, 2324-2346

Abstract: Abstract The topic of this paper includes graph cuts based computed tomography reconstruction methods in binary and multi-gray level cases. This approach combines the graph cuts and a gradient based method. The present paper introduces and analyses the shape circularity as a new regularization and incorporates it in a graph cuts based computed tomography reconstruction approach, thus introducing a new energy-minimization based reconstruction algorithm for binary tomography. Proposed method is capable for reconstructions in cases of limited projection view availability. Results of experimental evaluation of the considered graph cuts type reconstruction methods for both binary and multi-level tomography are presented.

Keywords: Discrete tomography; Binary tomography; Shape circularity; Graph cuts optimization; Energy minimization methods (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10878-021-00730-4

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