Paper
19 March 2013 Radiation dose reduction and CNR enhancement in C-arm cone beam CT
Kai Niu, Jie Tang, Kevin Royalty, Orhan Ozkan, Charles Strother, Beverly Aagaard-Kienitz, Kari A. Pulfer, Guang-Hong Chen
Author Affiliations +
Proceedings Volume 8668, Medical Imaging 2013: Physics of Medical Imaging; 86682S (2013) https://doi.org/10.1117/12.2007736
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States
Abstract
In this work we applied dose reduction using the prior image constrained compress sensing (DR-PICCS) method on a C-arm cone beam CT system. DR-PICCS uses a smoothed image as the prior image. After applying DRPICCS, the final image will have noise variance inherited from the prior image and spatial resolution from the projection data. In order to investigate the dose reduction of DR-PICCS, three different dose levels were used in C-arm scans of animal subjects using a Siemens Zeego C-arm system under an IACUC protocol. Image volumes were reconstructed using the standard FBP and DR-PICCS algorithms(total of 160 images). These images were randomly mixed and presented to three experienced interventional radiologists(each having more than twenty years reading experience) to review and score using a five-point scale. After statistical significance testing, the results show that DR-PICCS can achieve more than 60% dose reduction while keeping the same image quality. And if we compare FBP and DR-PICCS at the same dose level the results show that DR-PICCS will generate higher quality images.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kai Niu, Jie Tang, Kevin Royalty, Orhan Ozkan, Charles Strother, Beverly Aagaard-Kienitz, Kari A. Pulfer, and Guang-Hong Chen "Radiation dose reduction and CNR enhancement in C-arm cone beam CT", Proc. SPIE 8668, Medical Imaging 2013: Physics of Medical Imaging, 86682S (19 March 2013); https://doi.org/10.1117/12.2007736
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Cited by 2 scholarly publications.
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KEYWORDS
Image quality

Spatial resolution

Image compression

Reconstruction algorithms

Denoising

Image quality standards

Computed tomography

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