PET Count Loss Correction via Block-Specific Single-Photon Factors
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Solution Overview
Problem
Current methods for correcting count loss in PET systems suffer from low accuracy, leading to degraded image quality due to differences in single-photon distribution between the phantom used during modeling and clinical scanning, resulting in incorrect correction factors and inaccurate true coincidence count rates.
Innovation Solution
A method involving a modeling stage to build functional relationships between single-photon count rates and correction factors for each Block, and a clinical scanning stage to apply these corrections, accounting for single-photon and coincidence loss factors to eliminate distribution differences and improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a phantom is used during modeling to build correction factors, then the correction model can be established, but differences in single-photon distribution between the phantom and clinical scanning lead to inaccurate correction factors
Solution Approach 1:
The detector is divided into multiple Blocks, and correction factors are built for each Block separately based on its specific single-photon count rate characteristics. This segmentation allows each Block to be corrected according to its own distribution patterns rather than using a uniform correction approach, thereby resolving the inconsistency between phantom modeling and clinical scanning.
Solution Approach 2:
The patent implements local quality by making correction factors specific to each Block's single-photon count rate rather than using a global correction factor for the entire detector. This localized approach ensures that each Block receives appropriate correction based on its specific characteristics, improving the accuracy of true coincidence count rate correction.
2Measurement precision
If traditional count loss correction methods are used, then the processing is simple, but the accuracy of true coincidence count rates is degraded
Solution Approach 1:
The patent performs preliminary action by building functional relationships between single-photon count rates and correction factors for each Block during a modeling stage using a phantom. This pre-established correction model is then applied during clinical scanning, separating the complex model development from the actual clinical correction process and maintaining high accuracy without complicating the clinical workflow.
Solution Approach 2:
The patent introduces an intermediary functional relationship model that connects single-photon count rates to correction factors. This intermediary model serves as a bridge between the measured single-photon count rates and the required true coincidence count rate corrections, enabling accurate correction while maintaining a structured and manageable correction process.
Data Source
AI summary
Methods for correcting a count loss and PET systems are provided according to examples of the present disclosure. In one aspect, the PET system obtain scanning data of a subject to be detected for which random correction has been performed, obtain a first correction factor corresponding to the true coincidence count according to the single-photon count rates of the two Blocks corresponding to the true coincidence count, obtain a second correction factor corresponding to the true coincidence count according to the system single-photon count rate, and correct the true coincidence count according to the first correction factor and the second correction factor corresponding to the true coincidence count.