Effect of scattered radiation on image noise in cone beam CT
- PMID: 11339743
- DOI: 10.1118/1.1357457
Effect of scattered radiation on image noise in cone beam CT
Abstract
Cone beam CT has a capability for the 3-dimensional imaging of large volumes with isotropic resolution, and has a potentiality for 4-dimensional imaging (dynamic volume imaging), because cone beam CT acquires data of a large volume with one rotation of an x-ray tube-detector pair. However, one of the potential drawbacks of cone beam CT is a larger amount of scattered x-rays, which may enhance the noise in reconstructed images, and thus affect the low-contrast detectablity. Our aim in this work was to estimate the scatter fractions and effects of scatter on image noise, and to seek methods of improving image quality in cone beam CT. First we derived a relationship between the noise in a reconstructed image and in an x-ray intensity measurement. Then we estimated the scatter to primary ratios in x-ray measurements using a Monte-Carlo simulation. From these we estimated the image noise under relevant clinical conditions. The results showed that the scattered radiation made a substantial contribution to the image noise. However, focused collimators could improve it by decreasing the scattered radiation drastically while keeping the primary radiation at nearly the same level. A conventional grid also improved the image noise, though the improvement was less than that of focused collimators.
Similar articles
-
Simulated scatter performance of an inverse-geometry dedicated breast CT system.Med Phys. 2009 Mar;36(3):788-96. doi: 10.1118/1.3077165. Med Phys. 2009. PMID: 19378739
-
X-ray scatter correction for multi-source interior computed tomography.Med Phys. 2017 Jan;44(1):71-83. doi: 10.1002/mp.12022. Med Phys. 2017. PMID: 28102959
-
Cone-beam breast computed tomography with a displaced flat panel detector array.Med Phys. 2012 May;39(5):2805-19. doi: 10.1118/1.4704641. Med Phys. 2012. PMID: 22559652
-
Imaging modalities in x-ray computerized tomography and in selected volume tomography.Phys Med Biol. 1999 Mar;44(3):R23-56. doi: 10.1088/0031-9155/44/3/011. Phys Med Biol. 1999. PMID: 10211798 Review.
-
Revisiting the need for radiation output measurements after X-ray tube replacement in computed tomography.J Appl Clin Med Phys. 2021 Aug;22(8):230-235. doi: 10.1002/acm2.13359. Epub 2021 Jul 19. J Appl Clin Med Phys. 2021. PMID: 34288365 Free PMC article. Review.
Cited by
-
Cone beam CT multisource configurations: evaluating image quality, scatter, and dose using phantom imaging and Monte Carlo simulations.Phys Med Biol. 2020 Dec 18;65(23):235032. doi: 10.1088/1361-6560/abc306. Phys Med Biol. 2020. PMID: 33080583 Free PMC article.
-
The impact of manual threshold selection in medical additive manufacturing.Int J Comput Assist Radiol Surg. 2017 Apr;12(4):607-615. doi: 10.1007/s11548-016-1490-4. Epub 2016 Oct 7. Int J Comput Assist Radiol Surg. 2017. PMID: 27718124 Free PMC article.
-
Paired cycle-GAN-based image correction for quantitative cone-beam computed tomography.Med Phys. 2019 Sep;46(9):3998-4009. doi: 10.1002/mp.13656. Epub 2019 Jul 17. Med Phys. 2019. PMID: 31206709 Free PMC article.
-
Noise-resolution tradeoffs in x-ray CT imaging: a comparison of penalized alternating minimization and filtered backprojection algorithms.Med Phys. 2011 Mar;38(3):1444-58. doi: 10.1118/1.3549757. Med Phys. 2011. PMID: 21520856 Free PMC article.
-
Deep learning-based 3D brain multimodal medical image registration.Med Biol Eng Comput. 2024 Feb;62(2):505-519. doi: 10.1007/s11517-023-02941-9. Epub 2023 Nov 8. Med Biol Eng Comput. 2024. PMID: 37938452
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical