Optimum filtration for time-activity curves in nuclear medicine

Insufficient filtration and over-smoothing are misleading processes in the quantification of time-activity curves. The optimum filtration requires a g ood knowledge of the frequency spectrum and relative amplitudes of the data and superimposed noise. Due to variations in biomedical data, it is very d ifficult to adjust the filter for individual cases. To overcome this proble m a new method of noise reduction is proposed. In this method the time-acti vity curves are transformed into a low frequency (linear) curve that can be filtered heavily without significant distortion of the real data. The theo ry of the proposed filter and the results of its comparison with three-poin t filter, five-point filter and data bounding methods are presented. The co mparison 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 e rror and the peak of the renogram. Moreover, the filter is much less sensit ive to over-smoothing (number of filter iterations), the signal-to-noise ra tio and the mean transit time of the renogram compared with other filters. ((C) 2000 Lippincott Williams & Wilkins).