Iterative Image Reconstruction Methods applied to data from a prototype small-animal PET
2007
The purpose of this study is to evaluate the average performance of algebraic and statistical iterative reconstruction methods, using phantom data from a prototype small-animal PET system. The algorithms that are being compared are the simultaneous versions of ART (SART) and MART (SMART), EM-ML, ISRA and WLS. The evaluation study was based on reconstructed image quality, as it is derived from visual inspection, normalized profiles, cross-correlation coefficient and CNRs (contrast-to-noise ratios) of specific ROIs (region-of-interest). In general EM-ML and ISRA present similar reconstruction time and minor differences in reconstructed image quality. Slightly superior performances show WLS and SART while SMART is not adequate for reconstruction of PET data.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
0
References
0
Citations
NaN
KQI