Haase V, Noo F, Stierstorfer K, Maier A, McNitt-Gray M (2022)
Publication Type: Conference contribution
Publication year: 2022
Publisher: SPIE
Book Volume: 12304
Conference Proceedings Title: Proceedings of SPIE - The International Society for Optical Engineering
Event location: Online
ISBN: 9781510656697
DOI: 10.1117/12.2646523
Reproducibility of CT numbers represents an ongoing challenge, especially in clinical applications where exams are performed to assess disease progression or response to therapy. Dual energy CT (DECT) offers an opportunity for improved image quantification, but also presents unique issues. This work presents an initial phantom study that investigates reproducibility over time, across different scanners, and with regard to positioning of the phantom. Both an image domain and a projection data domain material decomposition method are used to create mono-energetic images from DECT data. The scanned object is the ACR CT accreditation phantom. Images were evaluated for reproducibility both inside the phantom inserts of module A as well as in regions between the inserts, where image artifacts are frequently visualized. The results demonstrate that artifacts are worse for off-centered positions. They also demonstrate that the data-based material decomposition provides comparable HU numbers within the inserts of interest like the image-based method, but provides substantially less artifacts and less HU variability in regions surrounding the inserts across the different phantom positions.
APA:
Haase, V., Noo, F., Stierstorfer, K., Maier, A., & McNitt-Gray, M. (2022). Reproducibility in dual energy CT: the impact of a projection domain material decomposition method. In Joseph Webster Stayman (Eds.), Proceedings of SPIE - The International Society for Optical Engineering. Online: SPIE.
MLA:
Haase, V., et al. "Reproducibility in dual energy CT: the impact of a projection domain material decomposition method." Proceedings of the 7th International Conference on Image Formation in X-Ray Computed Tomography, Online Ed. Joseph Webster Stayman, SPIE, 2022.
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