Bone SPECT image reconstruction using deconvolution and wavelet transformation: development, performance assessment and comparison in phantom and patient study with standard OSEM and resolution recovery algorithm

Abstract

Purpose: The aim of this work was to introduce a new algorithm for image reconstruction in bone SPECT and to compare its performances with a commercially available standard OSEM and resolution recovery (RR) reconstruction.

Materials and methods: The algorithm was built applying the Lucy-Richardson deconvolution adn logarithmic image processing to the projections. A modification of the coefficients of wavelet decomposition was used to suppress the noise. The comparison with vendor software was performed both in a phantom study, using Signal-to-Noise ratio (SNR), Signal-to-Background ratio (SBR), spatial resolution and in clinical studies, by visual assessment of changes in contrast, spatial resolution and lesion detectability.

Results: A change in the SNR (from -4 to 40%), an increase in the SBR (from 19 to 40%), a minor improvement in spatial resolution and a similar noise level were observed in the phantom study in comparison to the standard OSEM. A decrease in the SNR, a worse spatial resolution, but only a 3 to 13 % lower SBR were achieved in comparison with the vendor supplied RR algorithm. The proposed algorithm creates patient images with better contrast and lesion detectability compared to clinically used OSEM. Compared to RR, more than half of obtained images showed better contrast and nearly half of them have better lesion detectability.

Conclusion: The proposed algorithm compares favorably with the standard OSEM. Although less favorable, the comparison with RR and noise suppression algorithms, suggests that it can be used with only a slight decrease in the SBR.

Keywords: Deconvolution; Logarithmic image processing; Wavelet denoising.