Monitored Reconstruction: Computed Tomography as an Anytime Algorithm
Computed tomography is an important technique for non-destructive analysis of an object’s internal structure, relevant for scientific studies, medical applications, and industry. Pressing challenges emerging in the field of tomographic imaging include speeding up reconstruction, reducing...
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9115485/ |
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| author | Konstantin Bulatov Marina Chukalina Alexey Buzmakov Dmitry Nikolaev Vladimir V. Arlazarov |
| author_facet | Konstantin Bulatov Marina Chukalina Alexey Buzmakov Dmitry Nikolaev Vladimir V. Arlazarov |
| author_sort | Konstantin Bulatov |
| collection | DOAJ |
| description | Computed tomography is an important technique for non-destructive analysis of an object’s internal structure, relevant for scientific studies, medical applications, and industry. Pressing challenges emerging in the field of tomographic imaging include speeding up reconstruction, reducing the time required to obtain the X-ray projections, and reducing the radiation dose imparted to the object. In this paper, we introduce a model of a monitored reconstruction process, in which the acquiring of projections is interspersed with image reconstruction. This model allows to examine the tomographic reconstruction process as an anytime algorithm and consider a problem of finding the optimal stopping point, corresponding to the required number of X-ray projections for the currently scanned object. We outline the theoretical framework for the monitored reconstruction, propose ways of constructing stopping rules for various reconstruction quality metrics and provide their experimental evaluation. Due to stopping at different times for different objects, the proposed approach allows to achieve a higher mean reconstruction quality for a given mean number of X-ray projections. Conversely, fewer projections on average are used to achieve the same mean reconstruction quality. |
| format | Article |
| id | doaj-art-3d05fc7c2eea403d96ac132b1dde902c |
| institution | Matheson Library |
| issn | 2169-3536 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-3d05fc7c2eea403d96ac132b1dde902c2025-07-02T00:05:37ZengIEEEIEEE Access2169-35362020-01-01811075911077410.1109/ACCESS.2020.30020199115485Monitored Reconstruction: Computed Tomography as an Anytime AlgorithmKonstantin Bulatov0https://orcid.org/0000-0003-1644-5162Marina Chukalina1https://orcid.org/0000-0002-1410-5175Alexey Buzmakov2https://orcid.org/0000-0003-0539-5606Dmitry Nikolaev3https://orcid.org/0000-0001-5560-7668Vladimir V. Arlazarov4https://orcid.org/0000-0003-3260-9104Federal Research Center “Computer Science and Control”, Russian Academy of Sciences, Moscow, RussiaSmart Engines Service LLC, Moscow, RussiaSmart Engines Service LLC, Moscow, RussiaSmart Engines Service LLC, Moscow, RussiaFederal Research Center “Computer Science and Control”, Russian Academy of Sciences, Moscow, RussiaComputed tomography is an important technique for non-destructive analysis of an object’s internal structure, relevant for scientific studies, medical applications, and industry. Pressing challenges emerging in the field of tomographic imaging include speeding up reconstruction, reducing the time required to obtain the X-ray projections, and reducing the radiation dose imparted to the object. In this paper, we introduce a model of a monitored reconstruction process, in which the acquiring of projections is interspersed with image reconstruction. This model allows to examine the tomographic reconstruction process as an anytime algorithm and consider a problem of finding the optimal stopping point, corresponding to the required number of X-ray projections for the currently scanned object. We outline the theoretical framework for the monitored reconstruction, propose ways of constructing stopping rules for various reconstruction quality metrics and provide their experimental evaluation. Due to stopping at different times for different objects, the proposed approach allows to achieve a higher mean reconstruction quality for a given mean number of X-ray projections. Conversely, fewer projections on average are used to achieve the same mean reconstruction quality.https://ieeexplore.ieee.org/document/9115485/Anytime algorithmscomputed tomographydose reductionmonitored reconstructionoptimal stoppingX-ray tomography |
| spellingShingle | Konstantin Bulatov Marina Chukalina Alexey Buzmakov Dmitry Nikolaev Vladimir V. Arlazarov Monitored Reconstruction: Computed Tomography as an Anytime Algorithm IEEE Access Anytime algorithms computed tomography dose reduction monitored reconstruction optimal stopping X-ray tomography |
| title | Monitored Reconstruction: Computed Tomography as an Anytime Algorithm |
| title_full | Monitored Reconstruction: Computed Tomography as an Anytime Algorithm |
| title_fullStr | Monitored Reconstruction: Computed Tomography as an Anytime Algorithm |
| title_full_unstemmed | Monitored Reconstruction: Computed Tomography as an Anytime Algorithm |
| title_short | Monitored Reconstruction: Computed Tomography as an Anytime Algorithm |
| title_sort | monitored reconstruction computed tomography as an anytime algorithm |
| topic | Anytime algorithms computed tomography dose reduction monitored reconstruction optimal stopping X-ray tomography |
| url | https://ieeexplore.ieee.org/document/9115485/ |
| work_keys_str_mv | AT konstantinbulatov monitoredreconstructioncomputedtomographyasananytimealgorithm AT marinachukalina monitoredreconstructioncomputedtomographyasananytimealgorithm AT alexeybuzmakov monitoredreconstructioncomputedtomographyasananytimealgorithm AT dmitrynikolaev monitoredreconstructioncomputedtomographyasananytimealgorithm AT vladimirvarlazarov monitoredreconstructioncomputedtomographyasananytimealgorithm |