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 imaginary 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.
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 imaginary 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.
Authors: F E Turkheimer; M Brett; J A Aston; A P Leff; P A Sargent; R J Wise; P M Grasby; V J Cunningham Journal: J Cereb Blood Flow Metab Date: 2000-11 Impact factor: 6.200
Authors: A Cagnin; D J Brooks; A M Kennedy; R N Gunn; R Myers; F E Turkheimer; T Jones; R B Banati Journal: Lancet Date: 2001-08-11 Impact factor: 79.321
Authors: Alexander N Anderson; Nicola Pavese; Paul Edison; Yan F Tai; Alexander Hammers; Alexander Gerhard; David J Brooks; Federico E Turkheimer Journal: Neuroimage Date: 2007-02-21 Impact factor: 6.556
Authors: Akihiro Takano; Fredrik Piehl; Jan Hillert; Andrea Varrone; Sangram Nag; Balázs Gulyás; Per Stenkrona; Victor L Villemagne; Christopher C Rowe; Richard Macdonell; Nabil Al Tawil; Thomas Kucinski; Torsten Zimmermann; Marcus Schultze-Mosgau; Andrea Thiele; Anja Hoffmann; Christer Halldin Journal: EJNMMI Res Date: 2013-04-24 Impact factor: 3.138