PET Detection Timing Correction With Light-Emission Probability Models
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Solution Overview
Problem
Existing PET image reconstruction methods face challenges in achieving accurate estimation of the time from gamma ray incidence to light emission, which is crucial for improving the accuracy of Time of Flight (ToF) kernel performance, and require significant computational resources for neural network-based learning.
Innovation Solution
A nuclear medicine diagnostic device employs a light emission probability model to estimate the detection timing of events, using photon-number information to correct detection timings and sharpen the ToF spectrum, reducing the need for extensive computational resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If neural network-based learning is used to estimate detection timing, then estimation accuracy improves, but computational resources required increase significantly
Solution Approach 1:
The patent replaces the expensive neural network model with a simpler, computationally inexpensive light emission probability model that can be calculated quickly without requiring extensive machine learning training, thereby reducing computational resource consumption while maintaining acceptable estimation accuracy
Solution Approach 2:
The patent extracts only the essential physical relationship (light emission probability based on photon detection) from the complex neural network approach, creating a simplified model that retains the core functionality while eliminating unnecessary computational complexity
2Manufacturing precision
If ToF kernel accuracy is improved for PET image reconstruction, then image quality improves, but the complexity of the reconstruction process increases
Solution Approach 1:
The patent changes the parameter estimation approach from complex neural network-based detection timing estimation to a simpler light emission probability model based on photon detection, thereby improving ToF kernel accuracy while reducing reconstruction process complexity
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The proposed method enhances the accuracy of PET image reconstruction by sharpening the ToF spectrum and improving image quality without the need for extensive computational resources.
Implementation Method 1
the period of time starting from the incidence of gamma rays onto a scintillator till the occurrence of light emission
Data Source
AI summary
A nuclear medicine diagnostic device according to an embodiment includes processing circuitry. The processing circuitry obtains first photon-number information detected by a first detector; calculates, based on the first photon-number information, a first light emission probability model corresponding to the first detector; identifies, based on the first light emission probability model, a first timing at which the detection probability becomes equal to or greater than a predetermined threshold value; measures the detection timing of an event detected by the first detector; and corrects the detection timing based on the first timing.