Title :
Image oscillation reduction and convergence acceleration for OS-EM reconstruction [PET imaging]
Author :
Huang, Sung-Cheng
Author_Institution :
Sch. of Med., California Univ., Los Angeles, CA, USA
fDate :
6/1/1999 12:00:00 AM
Abstract :
Investigates the use of two approaches to reduce the image oscillation of OS-EM (ordered subset expectation maximization) reconstruction that is due to the inconsistencies among different partial subsets of the projection measurements (the sinogram) when considering as a group. One approach pre-processes the sinogram to make it satisfy a sinogram consistency condition. The second approach takes the average of the intermediary images (i.e. it smoothes image values over sub-iterations). Both approaches were found to be capable of reducing the image oscillation, and a combination of both was most effective. With these approaches, the convergence of OS-EM reconstruction is further improved. For computer-simulated data and real PET data, a single iteration of this new OS-EM reconstruction was shown to yield images comparable to those with 80 EM iterations
Keywords :
convergence of numerical methods; digital simulation; image reconstruction; iterative methods; medical image processing; optimisation; oscillations; positron emission tomography; smoothing methods; OS-EM image reconstruction; PET data; computer-simulated data; convergence acceleration; image oscillation reduction; image value smoothing; intermediary image averaging; ordered subset expectation maximization; partial subset inconsistencies; positron emmission tomography; projection measurements; sinogram consistency condition; sinogram preprocessing; sub-iterations; Acceleration; Biomedical imaging; Computer simulation; Convergence; Image reconstruction; Noise measurement; Pixel; Positron emission tomography; Time measurement; Uninterruptible power systems;
Journal_Title :
Nuclear Science, IEEE Transactions on
