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Proceedings Paper

Image denoising of low-radiation dose coronary CT angiography by an adaptive block-matching 3D algorithm
Author(s): Dongwoo Kang; Piotr Slomka; Ryo Nakazato; Jonghye Woo; Daniel S. Berman; C.-C. Jay Kuo; Damini Dey
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Paper Abstract

Our aim in this study was to optimize and validate an adaptive denoising algorithm based on Block-Matching 3D, for reducing image noise and improving assessment of left ventricular function from low-radiation dose coronary CTA. In this paper, we describe the denoising algorithm and its validation, with low-radiation dose coronary CTA datasets from 7 consecutive patients. We validated the algorithm using a novel method, with the myocardial mass from the low-noise cardiac phase as a reference standard, and objective measurement of image noise. After denoising, the myocardial mass were not statistically different by comparison of individual datapoints by the students' t-test (130.9±31.3g in low-noise 70% phase vs 142.1±48.8g in the denoised 40% phase, p= 0.23). Image noise improved significantly between the 40% phase and the denoised 40% phase by the students' t-test, both in the blood pool (p <0.0001) and myocardium (p <0.0001). In conclusion, we optimized and validated an adaptive BM3D denoising algorithm for coronary CTA. This new method reduces image noise and has the potential for improving assessment of left ventricular function from low-dose coronary CTA.

Paper Details

Date Published: 13 March 2013
PDF: 6 pages
Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86692G (13 March 2013); doi: 10.1117/12.2006907
Show Author Affiliations
Dongwoo Kang, Univ. of Southern California (United States)
Piotr Slomka, Cedars-Sinai Medical Ctr. (United States)
Ryo Nakazato, Cedars-Sinai Medical Ctr. (United States)
Jonghye Woo, Univ. of Maryland (United States)
Daniel S. Berman, Cedars-Sinai Medical Ctr. (United States)
C.-C. Jay Kuo, Univ. of Southern California (United States)
Damini Dey, Cedars-Sinai Medical Ctr. (United States)


Published in SPIE Proceedings Vol. 8669:
Medical Imaging 2013: Image Processing
Sebastien Ourselin; David R. Haynor, Editor(s)

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