Parametric imaging via kinetics-induced filter for dynamic positron emission tomography

Due to the noisy measurement of the voxel-wise time activity curve (TAC), parametric imaging for dynamic positron emission tomography (PET) is a challenging task. To address this problem, some spatial filters, such as Gaussian filter, bilateral filter, wavelet-based filter, and so on, are often performed to reduce the noise of each frame. However, these filters usually just consider local properties of each frame without exploring the kinetic information. In this paper, aiming to improve the quantitative accuracy of parametric imaging, we present a kinetics-induced filter to lower the noise of dynamic PET images by incorporating the kinetic information. The present kinetics-induced filter is designed via the similarity between voxel-wise TACs under the framework of bilateral filter. Experimental results with a simulation study demonstrate that the present kinetics-induced filter can achieve noticeable gains than other existing methods for parametric images in terms of quantitative accuracy measures.