Image reconstruction for dynamic PET based on low-order approximation and restoration of the sinogram

• Published in: IEEE transactions on medical imaging Vol. 16; no. 6; pp. 738 - 749
• Main Authors: Chien-Min Kao, Yap, J.T., Mukherjee, J., Wernick, M.N.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.12.1997; Institute of Electrical and Electronics Engineers
• Subjects: Algorithms; Animals; Approximation theory; Biological and medical sciences; Brain; Brain - diagnostic imaging; Brain - metabolism; Image enhancement; Image Processing, Computer-Assisted - methods; Image reconstruction; Image resolution; Image restoration; Investigative techniques, diagnostic techniques (general aspects); Least squares approximation; Macaca mulatta; Medical imaging; Medical sciences; Nervous system; Neurophysiology; Noise level; Noise reduction; Positron emission tomography; Principal component analysis; Radionuclide investigations; Receptors, Dopamine D2 - analysis; Reconstruction algorithms; Spatial resolution; Spurious signal noise; Tomography, Emission-Computed; Radionuclide study; Approximate method; Noise reduction; Monkey; Central nervous system; Dynamic conditions; Image reconstruction; Image quality; Vertebrata; Image analysis; Mammalia; D2 Dopamine receptor; Animal; Primates; Brain (vertebrata); Positron; Emission tomography
• ISSN: 0278-0062; 1558-254X
• DOI: 10.1109/42.650871

Many image-reconstruction methods have been proposed to improve the spatial resolution of positron emission tomography (PET) images and, thus, to produce better quantification. However, these techniques, which are designed for static images, may be inadequate for good reconstruction from dynamic data. The authors present a simple, but effective, reconstruction approach intended specifically for dynamic studies. First, the level of noise in dynamic PET data is reduced by smoothing along the time axis using a low-order approximation. Next, the denoised sinograms are restored spatially by the method of projections onto convex sets. Finally, images are reconstructed from the restored sinograms by ordinary filtered backprojection. The authors present experimental results that demonstrate substantial improvements in region-of-interest quantification in actual and simulated dopamine D-2 neuroreceptor-imaging studies of a monkey brain.