Abstract:
For quantitative PET, estimation of mean randoms from the measurement of delays relies on accurate estimate of the singles rates. For a continuous bed motion scan, the me...Show MoreMetadata
Abstract:
For quantitative PET, estimation of mean randoms from the measurement of delays relies on accurate estimate of the singles rates. For a continuous bed motion scan, the mean detector singles rates change constantly over time during the scan. The conventional formula based on detector singles rates involves averaging a nonlinear function of singles rates over time, which greatly increases the number of unknowns and the difficulty of estimation. In this work, a new formula for the CBM mean randoms was proposed, based on the object singles rates, which can be estimated by single-bed random smoothing algorithms. The object singles rates are singles rates measured by an ideal virtual scanner co-moving with the object and bed, reflecting the spatial distribution of singles rates within the object. Under approximations, a simplified approach was also derived, which requires no knowledge of the detector singles efficiencies, physical degrading factors, and acquisition parameters. Our method was evaluated by simulations on a Siemens next generation SiPM PET/CT prototype scanner with TOF mashing and by phantom measurements on a Siemens mCT PET/CT scanner. Unbiased estimations were obtained with much smaller variances than the raw delays. In conclusion, we developed a CBM randoms smoothing method which is based on the object randoms that can be estimated by the single-bed maximum likelihood algorithms. A simplified approach utilizes the fully 3D delays and leads to approximately unbiased estimates.
Date of Conference: 21-28 October 2017
Date Added to IEEE Xplore: 15 November 2018
ISBN Information: