PCCT Model Calibration with Phantom Scans for High-Flux Stability
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Solution Overview
Problem
Photon counting computed tomography (PCCT) technology is limited in clinical applications due to concerns over high-flux performance and stability at high clinical throughput, necessitating improved system calibration for enhanced accuracy.
Innovation Solution
A system and method for calibrating a PCCT system model by obtaining photon counting data from multiple phantoms, determining scanning and phantom parameters, and optimizing model parameters through iterative processes to establish a mapping relationship between photon counting data, scanning parameters, and reference material parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If PCCT technology is used for clinical applications, then improved spatial resolution and material discrimination are achieved, but high-flux performance and stability concerns limit wide clinical adoption
Solution Approach 1:
The patent applies preliminary action by performing system calibration before clinical applications. The calibration process uses phantom scans to determine system model parameters in advance, ensuring the system is properly configured and stable before actual patient imaging. This preliminary calibration step addresses reliability concerns by establishing known reference values that the system can use for accurate measurements during high-flux clinical operations.
2Measurement precision
If PCCT system model calibration is performed using multiple phantoms and iterative optimization, then model accuracy is enhanced, but system complexity and calibration time increase
Solution Approach 1:
The patent applies segmentation by dividing the calibration process into distinct components: system model definition, phantom scanning, data processing, and parameter optimization. The system model itself is segmented into multiple parameters (energy spectra, detection efficiency, charge sharing, pulse pileup) that can be independently determined and calibrated. This modular approach manages complexity by breaking down the overall calibration task into manageable, systematic steps.
3Measurement precision
If iterative optimization processes are used to determine model parameters, then calibration accuracy is improved, but calibration time and computational resources increase
Solution Approach 1:
The patent applies feedback through iterative optimization processes where the system model parameters are repeatedly adjusted based on comparisons between measured phantom data and simulated data. The optimization algorithm uses feedback from the error between actual and predicted measurements to refine parameters such as energy spectra, detection efficiency, and charge sharing effects. This feedback loop continues until convergence criteria are met, ensuring high calibration accuracy while systematically reducing the error with each iteration.
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
Enhances the accuracy and stability of PCCT systems, enabling improved material discrimination and quantitative analysis for clinical applications.
Implementation Method 1
photon counting computed tomography (PCCT) technology
Data Source
AI summary
A method may include obtaining a plurality of sets of photon counting data, each set of the plurality of sets of photon counting data being acquired by a photon counting computed tomography (PCCT) device scanning one of a plurality of phantoms according to one or more scanning parameters; obtaining a photon counting detector (PCD) system model of the PCCT device; and calibrating the PCCT system model by determining, based on the plurality of sets of photon counting data, the scanning parameters and phantom parameters of the phantom corresponding to each set of the plurality of sets of photon counting data, model parameters of the PCCT system model, the calibrated PCCT system model representing a mapping relationship between photon counting data, one or more scanning parameters, and one or more parameters of one or more reference materials through the determined model parameters.