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19 March 2014 Removing blooming artifacts with binarized deconvolution in cardiac CT
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Abstract
With modern CT scanners, detection and classification of coronary artery disease has become a routine applica- tion in cardiac CT. It poses a desirable non–invasive alternative to the invasive coronary angiography, which is the current clinical gold standard. However, the accuracy of cardiac CT depends on the spatial resolution of the imaging system. The limited spatial resolution leads to blooming artifacts, arising from hyper–dense calcification deposits in the arterial walls. This blooming leads to an overestimation of the degree of luminal narrowing and to loss of the morphology of the calcified region. We propose an image–based algorithm, which aims at removing the blooming and estimating the correct CT–value and morphology of the calcification. The method is based on the assumption, that each calcification consists of a compact region which has an almost constant density and attenuation. This knowledge is incorporated into an iterative deconvolution algorithm in image space. We quantitatively assess the accuracy of the proposed algorithm on analytically simulated phantom data. Qualita- tive results of clinical patient data are presented as well. In both cases, the proposed method outperforms the compared algorithms. The initial patient data results are promising. However, an ex vivo study has to be done to confirm the quantitative results of the simulation study with real specimen.
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Christian Hofmann, Michael Knaup, and Marc Kachelrieß "Removing blooming artifacts with binarized deconvolution in cardiac CT", Proc. SPIE 9033, Medical Imaging 2014: Physics of Medical Imaging, 90330J (19 March 2014); https://doi.org/10.1117/12.2036559
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