Statistical-based wavelet denoising technique for dynamic FDOPA-PET images analysis
Kang-Ping Lin, Hong-Dun Lin, Chin-Lung Yu, Liang-Chih Wu, Ren-Shyan Liu · 2002
In generally, the dynamic positron emission tomographic image (PET) that imaging with FDOPA plays as a powerful functional image tool to clinical diagnosis for the tissue disorders of Parkinson's disease. However, high noise is always shown in dynamic FDOPA, so that the accuracy of the pixel-based parametric image is not easy to achieve. To improve the quality problem of PET images, a novel subband denoising technique is provided in this paper. The method is based on the subband transformation and the statistical features in each subband of the PET image.