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首页> 外文期刊>Optik: Zeitschrift fur Licht- und Elektronenoptik: = Journal for Light-and Electronoptic >Feasibility of sinogram reconstruction based on inpainting method with decomposed sinusoid-like curve (S-curve) using total variation (TV) noise reduction algorithm in computed tomography (CT) imaging system: A simulation study
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Feasibility of sinogram reconstruction based on inpainting method with decomposed sinusoid-like curve (S-curve) using total variation (TV) noise reduction algorithm in computed tomography (CT) imaging system: A simulation study

机译:基于初始曲线(S曲线)在计算断层扫描(CT)成像系统中的分解正弦状曲线(S-CURVE)的初始正弦状曲线(S曲线)基于修复方法的可行性

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摘要

The use of computed tomography (CT) imaging system has increased significantly because it is very important role in the field of the medical diagnostic disease. However, CT has potential risk for high radiation dose and in addition to new strategy of reducing dose such as development of image reconstruction algorithm in sparse view conditions. Also, noise reduction is essential for improving image performance. In this study, with an aim to confirm feasibility of sinogram reconstruction based on inpainting method with decomposed sinusoid-like curve (S-curve) using total variation (TV) noise reduction algorithm in CT imaging system. For that purpose, we designed above-mentioned reconstruction and noise reduction algorithms and quantitatively evaluated coefficient of variation (COV), contrast to noise ratio (CNR) and root mean square error (RMSE). According to the results, our proposed image reconstruction method using TV noise reduction algorithm can acquire superb result in all evaluation parameters. The main benefit of our proposed method in sparse projection view is that it provides excellent image performance with efficient reconstruction in sinogram domain and noise reduction ratio. In conclusion, our results demonstrated that the better image performance using our proposed method can expect acquiring low scan time and low radiation dose. (C) 2018 Elsevier GmbH. All rights reserved.
机译:计算断层扫描(CT)成像系统的使用显着增加,因为它在医学诊断疾病领域是非常重要的作用。然而,CT具有高辐射剂量的潜在风险,并且除了在稀疏视野条件下降低图像重建算法的新策略之外。此外,降噪对于提高图像性能至关重要。在本研究中,目的是基于CT成像系统中的总变化(TV)降噪算法在初始化的正弦状曲线(S-CURVE)中基于采用分解的正弦状曲线(S曲线)来确认Scogram重建的可行性。为此目的,我们设计了上述重建和降噪算法和定量评估的变异系数(COV),与噪声比对比(CNR)和均方根误差(RMSE)。根据结果​​,我们所提出的使用TV降噪算法的图像重建方法可以在所有评估参数中获取SuperB结果。我们提出的稀疏投影视图中提出方法的主要好处是,它提供了优异的图像性能,在铭记域和降噪率中具有高效的重建。总之,我们的结果表明,使用我们所提出的方法更好的图像性能可以期望获得低扫描时间和低辐射剂量。 (c)2018年Elsevier GmbH。版权所有。

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