- Tytuł:
- A new statistical reconstruction method for the computed tomography using an X-ray tube with flying focal spot
- Autorzy:
-
Cierniak, Robert
Pluta, Piotr
Waligóra, Marek
Szymański, Zdzisław
Grzanek, Konrad
Pałka, Filip
Piuri, Vincenzo - Powiązania:
- https://bibliotekanauki.pl/articles/2031110.pdf
- Data publikacji:
- 2021
- Wydawca:
- Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
- Tematy:
-
computed tomography
iterative statistical reconstruction method
flying focal spot - Opis:
- This paper presents a new image reconstruction method for spiral cone- beam tomography scanners in which an X-ray tube with a flying focal spot is used. The method is based on principles related to the statistical model-based iterative reconstruction (MBIR) methodology. The proposed approach is a continuous-to-continuous data model approach, and the forward model is formulated as a shift-invariant system. This allows for avoiding a nutating reconstruction-based approach, e.g. the advanced single slice rebinning methodology (ASSR) that is usually applied in computed tomography (CT) scanners with X-ray tubes with a flying focal spot. In turn, the proposed approach allows for significantly accelerating the reconstruction processing and, generally, for greatly simplifying the entire reconstruction procedure. Additionally, it improves the quality of the reconstructed images in comparison to the traditional algorithms, as confirmed by extensive simulations. It is worth noting that the main purpose of introducing statistical reconstruction methods to medical CT scanners is the reduction of the impact of measurement noise on the quality of tomography images and, consequently, the dose reduction of X-ray radiation absorbed by a patient. A series of computer simulations followed by doctor’s assessments have been performed, which indicate how great a reduction of the absorbed dose can be achieved using the reconstruction approach presented here.
- Źródło:
-
Journal of Artificial Intelligence and Soft Computing Research; 2021, 11, 4; 271--286
2083-2567
2449-6499 - Pojawia się w:
- Journal of Artificial Intelligence and Soft Computing Research
- Dostawca treści:
- Biblioteka Nauki
Artykuł