Rajabi H, Pant G S
Department of Nuclear Medicine, All India Institute of Medical Sciences, Ansari Nagar, New Delhi.
Nucl Med Commun. 2000 Sep;21(9):823-8. doi: 10.1097/00006231-200009000-00007.
Insufficient filtration and over-smoothing are misleading processes in the quantification of time-activity curves. The optimum filtration requires a good knowledge of the frequency spectrum and relative amplitudes of the data and superimposed noise. Due to variations in biomedical data, it is very difficult to adjust the filter for individual cases. To overcome this problem a new method of noise reduction is proposed. In this method the time-activity curves are transformed into a low frequency (linear) curve that can be filtered heavily without significant distortion of the real data. The theory of the proposed filter and the results of its comparison with three-point filter, five-point filter and data bounding methods are presented. The comparison was performed using deconvolution analyses of simulated renograms. The results show that the proposed filter causes minimum distortion of the renogram and impulse retention function in terms of the root mean square error and the peak of the renogram. Moreover, the filter is much less sensitive to over-smoothing (number of filter iterations), the signal-to-noise ratio and the mean transit time of the renogram compared with other filters.
在时间-活性曲线的量化过程中，过滤不足和过度平滑是具有误导性的过程。最佳过滤需要对数据和叠加噪声的频谱及相对幅度有深入了解。由于生物医学数据存在变化，针对个别情况调整滤波器非常困难。为克服这一问题，提出了一种新的降噪方法。在该方法中，时间-活性曲线被转换为低频（线性）曲线，这样在对真实数据无显著失真的情况下可以进行大量滤波。文中介绍了所提出滤波器的理论以及它与三点滤波器、五点滤波器和数据边界方法比较的结果。该比较是通过对模拟肾图进行去卷积分析来进行的。结果表明，就均方根误差和肾图峰值而言，所提出的滤波器使肾图和脉冲保留函数的失真最小。此外，与其他滤波器相比，该滤波器对过度平滑（滤波器迭代次数）、信噪比和肾图的平均通过时间的敏感度要低得多。
