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. Single photon emission computed tomography (SPECT) is a non invasive functional imaging modality which enables in vivo examination of organs’ function. 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. The method proposed to accelerate the reconstruction as well as improve the quality of reconstructed images includes two steps: pre-processing step using different filtering conditions and a reconstruction step based on a ramp 3D Back Projection implementation. 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. In our future research we intend to concentrate on the preprocessing step of the proposed technique, more tests will be needed to enhance the quality of the tomography bone SPECT image reconstruction and devoid completely of artifacts.
Author(s) Details:
Afef Houimli,
University of Tunis El Manar, Higher Institute of Medical Technologies of Tunis, Research Laboratory in Biophysics and Medical Technologies LR13ES07, Tunis, 1006, Tunisia.
Please see the link here: https://stm.bookpi.org/NVMMS-V3/article/view/13955
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