Edge detection from X‐ray tomographic data for geometric image registration
In this paper, we propose new variational model for image registration from tomographic data. First, we employ the topological gradient approach for a tomographic reconstruction that uses the first‐ and the second‐order discontinuities in order to detect important objects of a given observed X‐ray t...
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Veröffentlicht in: | Mathematical methods in the applied sciences 2023-04, Vol.46 (6), p.6324-6358 |
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Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | In this paper, we propose new variational model for image registration from tomographic data. First, we employ the topological gradient approach for a tomographic reconstruction that uses the first‐ and the second‐order discontinuities in order to detect important objects of a given observed X‐ray tomographic data (sinograms). Second, we use this geometric information furnished by a high‐order operator in order to define an appropriate fidelity measure for the image registration process. A theoretical study of the proposed model is provided; Gauss–Newton method and multilevel technique are used for its numerical implementation. The performed numerical experiments show the efficiency and effectiveness of our model. |
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ISSN: | 0170-4214 1099-1476 |
DOI: | 10.1002/mma.8905 |