Fast Algorithm for the Determination of the Optimum Filter for Bone SPECT Image Reconstruction

Author(s): Afef houimli, Dorra Ben-sellem

In SPECT, the reconstructed images are strongly affected by poisson noise, poor spatial resolution and bad contrast due to the radioactivity disintegration and procedures acquisition. In this paper, we propose an algorithm to improve the traditional FBP reconstruction and to choose the most suitable technique for bone SPECT image denoising. The proposed approach is composed of two steps. The first one consists of denoising the acquired sinograms using successively eight currently used filters in nuclear medicine: Wiener, Metz, Hamming, Hann, Shepp-Logan, Parzen, Butterworth and Gaussian combined with Butterworth filters. The second step is a simultaneous reconstruction of the axial slices using a new 3D FBP algorithm for each filter. A comparative study of these filters is tested and evaluated on a dataset containing thirty one bone SPECT image. The results show that the difference between these filters is statistically significantly different from each other (p<0.05) and the 3D FBP with the combination between Butterworth and Gaussian provide the best performance. The selected method is compared to three denoising methods. These methods are tested on a Shepp Logan phantom and bone SPECT images. Experimental results show that the 3D FBP reconstruction with the pre-processing combination (Gaussian (Std=0.3) + Butterworth (fc=0.47, ordre=3)) filter is more accurate and robust compared to other methods. It provides the highest performance in term of contrast, SNR, CNR ensuring a shorter processing time. It accelerates the reconstruction, reduces noise and artifacts while preserving detailed features. This approach could be considered as a valuable candidate to enhance the quality of the reconstructed bone SPECT image.