Poster + Paper
7 April 2023 Analytic helical cone-beam artifact reduction for CT
Lusik Cherkezyan, Brian Nett, Jed D. Pack, Zhye Yin, Jiang Hsieh, Jonathan S. Maltz
Author Affiliations +
Conference Poster
Abstract
Modern CT enables fast volumetric helical acquisition with collimations up to 80 mm. These fast acquisitions are desirable to reduce patient time in the scanner and thus the likelihood of motion during the scan, especially for pediatric patients. Traditional approximate analytic reconstruction methods produce cone-beam artifacts in wide-coverage helical scan modes. These artifacts limit the clinical utility of wide-coverage acquisitions, as lower collimations are often selected to reduce the influence of these artifacts. Here, we develop and demonstrate the merits of a fast and effective analytic method for helical cone-beam artifact reduction (CBAR) which is suitable for clinical CT reconstruction. The hybrid reconstruction method described here reconstructs two image volumes: one with lower image noise and one with lower levels of cone beam artifact. The images are then combined using a two-dimensional Fourier blending approach. We demonstrate the methods effectiveness using phantoms (uniform and anthropomorphic) and clinical image data from head and neck exams in which these artifacts are most visible. When compared with traditional weighting, helical CBAR exhibited: a quantitative reduction in cone-beam artifacts, comparable noise values in uniform water phantoms, and a Likert-score increase from 2.8/5 to 4.1/5 (over a range of neurological CT scan types, N = 9). In conclusion, the frequency-blending hybrid reconstruction for helical CBAR has been demonstrated to be both fast and effective, providing higher diagnostic confidence when reading images from wide-coverage acquisitions and potentially enabling more frequent use of shorter-duration, wide-coverage helical scan modes such as 80 mm collimation.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lusik Cherkezyan, Brian Nett, Jed D. Pack, Zhye Yin, Jiang Hsieh, and Jonathan S. Maltz "Analytic helical cone-beam artifact reduction for CT", Proc. SPIE 12463, Medical Imaging 2023: Physics of Medical Imaging, 124633J (7 April 2023); https://doi.org/10.1117/12.2654242
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KEYWORDS
Image restoration

Medical image reconstruction

Reconstruction algorithms

CT reconstruction

Collimation

Computed tomography

Analytics

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