Iterative restoration of SPECT projection images

Abstract

Photon attenuation and the limited non-stationary spatial resolution of the detector can reduce both qualitative and quantitative image quality in SPECT. Here, the authors describe a reconstruction approach which can compensate for both of these degradations. The approach involves processing the projection data with Bellini's method for attenuation compensation followed by an iterative deconvolution technique which uses the frequency distance principle (FDP) to model the distance-dependent camera blur. Modelling of the camera blur with the FDP allows an efficient implementation using FFT methods. After processing of the projection data, reconstruction is performed using filtered backprojection. Simulation studies using the Hoffman brain phantom show that this approach gives reconstructions with low bias and no visually undesirable noise artifact with a low computational overhead.