A wavelet-based SPECT reconstruction algorithm for nonuniformly attenuated Radon transform

Purpose: Single photon emission computed tomography (SPECT) is a tomography technique that can greatly show information about the metabolic activity in the body and improve the clinical diagnosis. In SPECT, because of photoelectric absorption and Compton scattering, the emitted gamma photons are attenuated inside the body before arriving at the detector. The goal of quantitative SPECT reconstruction is to obtain an accurate image of the radioactivity distribution in the interested area of a human body, so the compensation for nonuniform attenuation and the treatment of Poisson noise are necessary in the quantitative SPECT reconstruction. Methods: The authors know that the wavelet transform has characteristics of multiresolution and localized nature, and these characteristics can be applied for denoising and localized reconstruction. Based on the explicit inversion formula for the attenuated Radon transform, the authors present a wavelet-based SPECT reconstruction algorithm with compensation for nonuniform attenuation. Results: The wavelet-based SPECT reconstruction algorithm offers the ability for denoising in the reconstruction processing. In simulation, 128 projections were simulated evenly spaced over 360° by a circular orbit, each with 128 bins. Simulation results show that the wavelet-based denoising is effective in SPECT reconstruction. Conclusions: The authors present a wavelet-based SPECT reconstruction algorithm with compensation for nonuniform attenuation. The reconstruction results from computer simulations show that the wavelet-based SPECT reconstruction algorithm is accurate.