Noise properties of filtered-backprojection and ML-EM reconstructed emission tomographic images
- Univ. of North Carolina, Chapel Hill, NC (United States). Dept. of Biomedical Engineering
- Univ. of North Carolina, Chapel Hill, NC (United States). Dept. of Biomedical Engineering Univ. of North Carolina, Chapel Hill, NC (United States). Dept. of Radiology
The authors compared noise properties of emission tomographic images reconstructed using maximum likelihood-expectation maximization (ML-EM) and filtered-backprojection (FBP) algorithms. Noise comparisons were made in terms of the covariance matrix which gives information on the noise magnitude and noise correlations. They studied noise properties as a function of iteration for ML-EM and as a function of noise apodization filter for FBP. The authors show that FBP reconstruction spreads noise variance from image regions containing high count densities into regions of low count densities. They also demonstrate at lower FBP filter cutoff frequencies the noise is correlated over relatively long distances and the correlation function has deep negative side-lobes. For ML-EM reconstruction they show that little noise variance is spread from high count density regions into low count regions and that at lower iteration number the noise is correlated over shorter distances than for FBP. Also for ML-EM, the correlation function has no negative side-lobes at low iterations numbers, although as the iteration number increases the function begins to resemble the FBP correlation function. They conclude from these observations that ML-EM reconstruction offers properties which may exceed FBP in terms of detectability for certain emission tomographic imaging situations.
- OSTI ID:
- 6057481
- Journal Information:
- IEEE Transactions on Nuclear Science (Institute of Electrical and Electronics Engineers); (United States), Vol. 40:4 part 1; ISSN 0018-9499
- Country of Publication:
- United States
- Language:
- English
Similar Records
Precision and accuracy of regional radioactivity quantitation using the maximum likelihood EM reconstruction algorithm
Reducing negativity artifacts in emission tomography: Post-processing filtered backprojection solutions