What is it about?
Two few-view tomography algorithms that perform joint image reconstruction and segmentation are compared. They are the iterative Potts minimization algorithm (M. Storath et al. Inverse Problems 31: 025003, 2015) and the algebraic algorithm with TV-regularization and adaptive segmentation (V. V. Vlasov et al. J Electron Imaging 27: 043006, 2018).
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Why is it important?
Even in conditions of noisy projection data, the studied algorithms are capable of accurately reconstructing a tomographic image from less than 10 views.
Perspectives
Both algorithms should be tested in experiments with phantoms and in clinical conditions. The authors hope that effective tomogram reconstruction technologies for commercial systems can be created based on the algorithms.
Dr. Alexander B Konovalov
Federal State Unitary Enterprise “Russian Federal Nuclear Center – Zababakhin All-Russia Research Institute of Technical Physics,” Snezhinsk, Russia
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This page is a summary of: Joint image reconstruction and segmentation: Comparison of two algorithms for few-view tomography, Computer Optics, December 2019, Samara State Aerospace University,
DOI: 10.18287/2412-6179-2019-43-6-1008-1020.
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