Wavelet based de-noising methods for local SPECT reconstruction with non-uniform attenuation

In the conventional single photon emission computed tomography (SPECT), reconstruction algorithm requires full projection data to reconstruct the images, which will be time-consuming. While in clinic, doctors usually just care about the region of interest (ROI), such as heart, not whole body, in this case, a local SPECT reconstruction algorithm is needed to reconstruct the ROI by only using the projection data from the ROI. In SPECT, the non-stationary Possion noise in the projection data (sinogram) is a major cause to compromise the quality of the reconstructed images. To improve the reconstruction quality, we must remove the Possion noise in the sinogram before reconstruction. However, the conventional space or frequency domain de-noising methods possibly remove the edge information, which is very important for the accurate reconstruction, especially for the local SPECT reconstruction with non-uniform attenuation. Wavelet transform, due to its excellent localization property, has rapidly become an indispensable image processing tool for de-noising. In this paper, we tried to find out the properties of wavelet based de-noising methods for local SPECT reconstruction with non-uniform attenuation. From the de-noising results, we can see that wavelet based de-noising methods have good performance for local SPECT reconstruction.