18 March 2015 Improving low-dose cardiac CT images using 3D sparse representation based processing
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Abstract
Cardiac computed tomography (CCT) has been widely used in diagnoses of coronary artery diseases due to the continuously improving temporal and spatial resolution. When helical CT with a lower pitch scanning mode is used, the effective radiation dose can be significant when compared to other radiological exams. Many methods have been developed to reduce radiation dose in coronary CT exams including high pitch scans using dual source CT scanners and step-and-shot scanning mode for both single source and dual source CT scanners. Additionally, software methods have also been proposed to reduce noise in the reconstructed CT images and thus offering the opportunity to reduce radiation dose while maintaining the desired diagnostic performance of a certain imaging task. In this paper, we propose that low-dose scans should be considered in order to avoid the harm from accumulating unnecessary X-ray radiation. However, low dose CT (LDCT) images tend to be degraded by quantum noise and streak artifacts. Accordingly, in this paper, a 3D dictionary representation based image processing method is proposed to reduce CT image noise. Information on both spatial and temporal structure continuity is utilized in sparse representation to improve the performance of the image processing method. Clinical cases were used to validate the proposed method.
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Luyao Shi, Luyao Shi, Yang Chen, Yang Chen, Limin Luo, Limin Luo, } "Improving low-dose cardiac CT images using 3D sparse representation based processing", Proc. SPIE 9412, Medical Imaging 2015: Physics of Medical Imaging, 94122F (18 March 2015); doi: 10.1117/12.2081988; https://doi.org/10.1117/12.2081988
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