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9 May 1997 Efficient sinogram smoothing for dynamic neuroreceptor PET imaging
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Abstract
We have developed image-restoration techniques applicable to dynamic positron emission tomography that improve the visual quality and quantitative accuracy of neuroreceptor images. Starting wit data from a study of dopamine D-2 receptors in rhesus monkey striata using selective radioligands such as fallypride, we performed a novel effective 3D smoothing of the dynamic sinogram at a much lower computational cost than a truly 3D, adaptive smoothing. The processed sinogram was then input to a standard filtered back-projection algorithm and the resulting images were sharper and less noisy than images reconstructed from the unprocessed sinogram. Simulations were performed and the radioligand binding curves extracted from the restored images were found to be smoother and more accurate than those extracted form the unprocessed reconstructions. Comparison was also made to reconstructions from sinograms processed by the principal component analysis/projection onto convex sets algorithm.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiaochuan Pan, Patrick J. La Riviere, James Ye, J. Mukherjee, and Chin-Tu Chen "Efficient sinogram smoothing for dynamic neuroreceptor PET imaging", Proc. SPIE 3033, Medical Imaging 1997: Physiology and Function from Multidimensional Images, (9 May 1997); https://doi.org/10.1117/12.274038
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