A wavelet technique developed by researchers in Taiwan promises to rectify the principal downside of PET's otherwise precise physiological uptake: low signal to photon ratio due to photon noise.
A wavelet technique developed by researchers in Taiwan promises to rectify the principal downside of PET's otherwise precise physiological uptake: low signal to photon ratio due to photon noise.
Researchers at National Yang-Ming University in Taipei kept the resolution and contrast high for their PET images by processing the images through selected wavelet parameters, reducing almost half the coefficient of variation in the region of interest.
Denoising a PET image can be achieved through the transfer of signals from the spatial domain to the wavelet domain using wavelet transform. Fourier transform can transfer a signal from the temporal (spatial) domain to the frequency (spatial frequency) domain. But because the signal is in sinusoidal form, temporal information is lost after transformation (Comput Med Imaging Graph 2005;29(4):297-304).
The basis of the wavelet technique is a waveform of limited duration, however, so the temporal (spatial) information is retained after transformation. Wavelet transform provides different analytical results by scaling and shifting the mother wavelet and time-frequency localization.
The denoising procedure is composed of three steps. First, the wavelet is decomposed into several filters. Second, the row and column of the original image are then convoluted via groups of filters. After the decomposition of an image, a threshold is obtained using statistical calculation. By suitable thresholding of wavelet coefficients, the noise can be removed from the image. Finally, the image is reconstructed after inverse wavelet transform.
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