Purpose We evaluated the noise reduction capability of wavelet denoising for estimated binding potential (BP) images (k 3 /k 4 ) of the peripheral benzodiazepine receptor using 18 F-FEDAA1106 and nonlinear least-square fitting. Methods Wavelet denoising within a three-dimensional discrete dual-tree complex wavelet transform was applied to simulate data and clinical dynamic positron emission tomography images of 18 F-FEDAA1106. To eliminate noise components in wavelet coefficients, real and

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... nary coefficients for each subband were thresholded individually using NormalShrink. A simulated dynamic brain image of 18 F-FEDAA1106 was generated and Gaussian noise was added to mimic PET dynamic scan. The derived BP images were compared with true images using 156 rectangular regions of interest. Wavelet denoising was also applied to data derived from seven young normal volunteers. Results In the simulations, estimated BP by denoised image showed better correlation with the true BP values (Y=0.83X+ 0.94, r=0.80), although no correlation was observed in the estimates between noise-added and true images (Y=1.2X+ 0.78, r=0.49). For clinical data, there were visual improvements in the signal-to-noise ratio for estimated BP images. Conclusions Wavelet denoising improved the bias and reduced the variation of pharmacokinetic parameters for BP. Keywords Positron emission tomography . Kinetic analysis . Wavelet denoising . Peripheral benzodiazepine receptor . Parametric imaging (SRTM) in simulation studies. In a series of papers [1-6], Turkheimer et al. have performed the most rigorous analysis of the wavelet transform for dynamic PET data. For linear regression analysis such as the Patlak plot [3, 5] and Eur