基于噪声功率谱的CT图像噪声评价
发布时间：2018-07-16 14:49
【摘要】：目的设计并探讨基于噪声功率谱(NPS)的CT图像噪声评价方法。方法改变CT图像扫描参数以及重建参数获取图像,采用NPS与传统标准差(SD)两种方法对该图像进行噪声检测,并对比两种检测结果。结果 NPS曲线幅值与层厚和剂量成反比,与重建算法的增强程度成正比。重建算法、层厚和剂量对噪声指数的影响能够在NPS曲线上得到明显的体现。结论 NPS能够从幅值与频率方面反应噪声变化,与SD方法相结合可形成更为完善的噪声评价体系。
[Abstract]:Objective to design and discuss the noise evaluation method of CT image based on noise power spectrum (NPS). Methods the scanning parameters and reconstruction parameters of CT images were changed to obtain the images. The noise detection of the images was performed by NPS and traditional standard deviation (SD), and the two detection results were compared. Results the amplitude of NPS curve is inversely proportional to the thickness and dose of the layer and is directly proportional to the enhancement degree of the reconstruction algorithm. The reconstruction algorithm, the effect of thickness and dose on the noise index can be clearly reflected on the NPS curve. Conclusion NPS can respond to noise changes in terms of amplitude and frequency, and a more perfect noise evaluation system can be formed by combining with SD method.
【作者单位】： 南方医科大学生物医学工程学院;
【基金】：广州市行业工程中心建设项目(穗科信条[2010]13-1)
【分类号】：R814.42
本文编号：2126722
[Abstract]:Objective to design and discuss the noise evaluation method of CT image based on noise power spectrum (NPS). Methods the scanning parameters and reconstruction parameters of CT images were changed to obtain the images. The noise detection of the images was performed by NPS and traditional standard deviation (SD), and the two detection results were compared. Results the amplitude of NPS curve is inversely proportional to the thickness and dose of the layer and is directly proportional to the enhancement degree of the reconstruction algorithm. The reconstruction algorithm, the effect of thickness and dose on the noise index can be clearly reflected on the NPS curve. Conclusion NPS can respond to noise changes in terms of amplitude and frequency, and a more perfect noise evaluation system can be formed by combining with SD method.
【作者单位】： 南方医科大学生物医学工程学院;
【基金】：广州市行业工程中心建设项目(穗科信条[2010]13-1)
【分类号】：R814.42
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