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Tomography Reconstruction Based on Null Space Search

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Combinatorial Image Analysis (IWCIA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13348))

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Abstract

The paper introduces a new tomography reconstruction approach for gray and binary image reconstruction. The proposed method intends to find a solution by searching for the best linear combination of the basis vectors of the null space of the projection matrix. One of the advantages of the proposed approach is that the projection error remains always extremely low, practically equal to zero, during the reconstruction process. The method applies a gradient based optimization algorithm. A short experimental evaluation, including three relevant and well-know algorithms for comparison, is presented.

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Acknowledgement

Authors acknowledge the financial support of Department of Fundamental Sciences, Faculty of Technical Sciences, University of Novi Sad, in the frame of the Project “Primena opštih disciplina u tehničkim i informatičkim naukama”. T. Lukić also acknowledges support received from the Hungarian Academy of Sciences through the DOMUS project.

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Authors and Affiliations

  1. Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia

    Tibor Lukić & Tamara Kopanja

Authors
  1. Tibor Lukić
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  2. Tamara Kopanja
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Correspondence to Tibor Lukić .

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Editors and Affiliations

  1. State University of New York at Fredonia, Fredonia, NY, USA

    Reneta P. Barneva

  2. SUNY Buffalo State College, Buffalo, NY, USA

    Valentin E. Brimkov

  3. University of Messina, Messina, Italy

    Giorgio Nordo

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Lukić, T., Kopanja, T. (2023). Tomography Reconstruction Based on Null Space Search. In: Barneva, R.P., Brimkov, V.E., Nordo, G. (eds) Combinatorial Image Analysis. IWCIA 2022. Lecture Notes in Computer Science, vol 13348. Springer, Cham. https://doi.org/10.1007/978-3-031-23612-9_15

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  • DOI: https://doi.org/10.1007/978-3-031-23612-9_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-23611-2

  • Online ISBN: 978-3-031-23612-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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