Nevin Manimala Statistics

Model-based pulse pileup and charge sharing compensation for photon counting detectors: A simulation study

Med Phys. 2022 Jun 20. doi: 10.1002/mp.15779. Online ahead of print.


PURPOSE: We aim at developing a model-based algorithm that compensates for the effect of both pulse pileup (PP) and charge sharing (CS), and evaluate the performance using computer simulations.

METHODS: The proposed PCP algorithm for PP and CS compensation cascaded models for CS and PP we previously developed, maximizes Poisson log-likelihood, and uses an efficient 3-step exhaustive search. For comparison, we also developed LCP algorithm that combines models for a loss of counts (LC) and CS. Two types of computer simulation, slab-based and CT-based, were performed to assess the performance of both PCP and LCP with 200 mA and 800 mA, (300 μm)2 x 1.6 mm cadmium telluride detector, and a deadtime of 23 ns. A slab-based assessment used a pair of adipose and iodine with different thicknesses, attenuated x-rays, assessed the bias and noise of the outputs from one detector pixel; a CT-based assessment simulated a chest/cardiac scan and a head-and-neck scan using 3-D phantom and noisy cone-beam projections.

RESULTS: With the slab simulation, the PCP had little or no biases when the expected counts was sufficiently large, even though a probability of count loss (PCL) due to deadtime loss or pulse pileup was as high as 0.8. In contrast, the LCP had significant biases (>±2 cm of adipose) when the PCL was higher than 0.15. Biases were present with both PCP and LCP when the expected counts were less than 10-120 per datum, which was attributed to the fact that the maximum-likelihood did not approach the asymptote. The noise of PCP was within 8% from Cramér-Rao lower bounds for most cases, when no significant bias was present. The two CT studies essentially agreed with the slab simulation study. PCP had little or no biases in the estimated basis line integrals, reconstructed basis density maps, and synthesized monoenergetic CT images. But the LCP had significant biases in basis line integrals when x-ray beams passed through lungs and near the body and neck contours, where the PCL were above 0.15. As a consequence, basis density maps and monoenergetic CT images obtained by LCP had biases throughout the imaged space.

CONCLUSION: We have developed the PCP algorithm that uses the PP-CS model. When the expected counts were more than 10-120 per datum, the PCP algorithm was statistically efficient and successfully compensates for the effect of the spectral distortion due to both PP and CS providing little or no biases in basis line integrals, basis density maps, and monoenergetic CT images regardless of count-rates. In contrast, the LCP algorithm, which models a loss of count due to pileup, produces severe biases when incident count-rates are high and the PCL is 0.15 or higher. This article is protected by copyright. All rights reserved.

PMID:35722721 | DOI:10.1002/mp.15779

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