ProMeSCT: A Proximal Metric Algorithm for Spectral CT Article Swipe
Souhil Tairi
,
Sandrine Anthoine
,
Yannick Boursier
,
Mathieu Dupont
,
C. Morel
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1109/trpms.2020.3036028
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1109/trpms.2020.3036028
The acquisition of a set of spectral photon-counting computed tomography (spectral PC-CT) measurements aims at uncovering both the spatial and energetic characteristics of the imaged body, which widens the potential of tomography compared to classical computed tomography (CT). In the preclinical context, the use of polychromatic beams induces spectral mixing and, as a consequence, the reconstruction procedure requires specific algorithmic tools more complex than the standard ones used in CT. In this article, we propose a one-step inversion method to simultaneously separate and reconstruct the physical materials of an object observed in the context of spectral PC-CT. To do so, we carefully consider the underlying polychromatic model of the X-ray beam and combine it with a priori on the materials of the object to reconstruct. The simultaneous separation and reconstruction of materials is done by minimizing the resulting nonconvex ill-posed inverse problem. The dimensionality of the data and object materials worsens the computational complexity of the problem. We propose an efficient optimization algorithm based on a proximal forward-backward algorithm that is accelerated by a metric, which is specifically designed for spectral PC-CT. The efficiency of our method called ProMeSCT is demonstrated on results obtained on 3-D synthetic data with a simple regularization that encompasses the positivity of the quantities of interest.
Related Topics
Concepts
Algorithm
Tomography
Inverse problem
Regularization (linguistics)
A priori and a posteriori
Context (archaeology)
Spectral imaging
Computer science
Metric (unit)
Iterative reconstruction
Curse of dimensionality
Mathematics
Artificial intelligence
Physics
Optics
Mathematical analysis
Biology
Epistemology
Paleontology
Economics
Philosophy
Operations management
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/trpms.2020.3036028
- OA Status
- green
- Cited By
- 4
- References
- 45
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3094836612
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3094836612Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/trpms.2020.3036028Digital Object Identifier
- Title
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ProMeSCT: A Proximal Metric Algorithm for Spectral CTWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
- Publication date
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2020-11-04Full publication date if available
- Authors
-
Souhil Tairi, Sandrine Anthoine, Yannick Boursier, Mathieu Dupont, C. MorelList of authors in order
- Landing page
-
https://doi.org/10.1109/trpms.2020.3036028Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://hal.science/hal-03327374Direct OA link when available
- Concepts
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Algorithm, Tomography, Inverse problem, Regularization (linguistics), A priori and a posteriori, Context (archaeology), Spectral imaging, Computer science, Metric (unit), Iterative reconstruction, Curse of dimensionality, Mathematics, Artificial intelligence, Physics, Optics, Mathematical analysis, Biology, Epistemology, Paleontology, Economics, Philosophy, Operations managementTop concepts (fields/topics) attached by OpenAlex
- Cited by
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4Total citation count in OpenAlex
- Citations by year (recent)
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2024: 1, 2023: 2, 2021: 1Per-year citation counts (last 5 years)
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45Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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