研究目的
Implementation and validation of time-of-flight PET image reconstruction module for listmode and sinogram projection data in the STIR library.
研究成果
The study presented the validation of the addition of TOF reconstruction of listmode and sinogram data in the STIR library, demonstrating that TOF reconstruction performs better than non-TOF in terms of both CRC and SNR. The implementation will be distributed as open source in the next version of the STIR library.
研究不足
The current TOF implementation is slower than for non-TOF, as the TOF kernel modelling is applied on-the-fly on the non-TOF LOR elements. Future work includes implementing caching of the TOF system matrix for systems with sufficient available memory and modifying the ray-tracing algorithm to directly support TOF bins.
1:Experimental Design and Method Selection:
The study implemented support for TOF PET for both listmode and sinogram data in the STIR library, using simulated data from the GATE Monte Carlo toolbox.
2:Sample Selection and Data Sources:
Simulated data from the NEMA IQ phantom was used, with TOF configurations spanning from
3:2 to 6 ps. List of Experimental Equipment and Materials:
GATE Monte Carlo toolbox (v.
4:2), STIR library, Intel i7 Skylake 6700K processor with 16 GB RAM and SSD drive. Experimental Procedures and Operational Workflow:
The study compared the reconstruction of listmode and sinogram data, assessed the truncation of the TOF kernel along LORs, and evaluated the performance in terms of CRC and SNR.
5:Data Analysis Methods:
The comparison was performed in terms of relative absolute error using averaged images over 10 noise realizations.
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