Detector Lag Correction Algorithm for CT Flat Panel X-Ray Imaging
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Solution Overview
Problem
Computed Tomography systems with large flat panel digital x-ray detectors suffer from detector lag due to electron de-trapping from high density electronic defects, leading to non-uniform artifacts in reconstructed images, which existing correction methods fail to fully address, especially when assuming linearity and time invariance.
Innovation Solution
A method using an empirical model to estimate and correct for trap filling and emptying in the detector, implemented through a computer program that modifies the data based on the current and total number of traps, accounting for different time constants associated with charge trapping and release, thereby correcting for lag and gain effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If prior correction methods assume linear time invariant process, then correction algorithm is simple, but correction is incomplete and artifacts remain
Solution Approach 1:
The patent applies dynamics by transitioning from a static linear time invariant model to a dynamic model that adapts to changing detector conditions. The system continuously updates correction parameters based on real-time measurements of detector response, allowing the correction algorithm to adapt to non-linear and time-variant behavior of the detector traps.
Solution Approach 2:
The patent changes the parameters of the correction model from fixed linear coefficients to variable parameters that reflect the actual physical state of the detector. By measuring actual detector response characteristics and using these to adjust correction parameters, the system accounts for non-linear effects and time-variant behavior without requiring overly complex algorithms.
2Reliability
If hardware modification with built-in LEDs is implemented, then gain and lag effects are eliminated, but device complexity and manufacturing difficulty increase
Solution Approach 1:
The patent introduces an intermediary correction system that mediates between the detector and the imaging pipeline. Rather than modifying the detector hardware itself, a separate correction module processes the detector output, using measured correction parameters to compensate for lag and gain effects. This approach eliminates artifacts while keeping the detector structure unchanged.
Solution Approach 2:
The patent replaces the mechanical/hardware solution (built-in LEDs and physical trap saturation) with a computational/software-based correction system. By using algorithms that model and compensate for detector behavior, the system achieves the same artifact elimination goal without requiring hardware modifications to the detector assembly.
3Measurement precision
If detector operates with high density electronic defects, then detector sensitivity is maintained, but electron de-trapping causes significant lag and artifacts
Solution Approach 1:
The patent converts the harmful effect of electron de-trapping into a measurable and correctable phenomenon. By characterizing the trap behavior through measurements and incorporating this knowledge into the correction algorithm, the system uses the information about harmful defects to develop compensation strategies that eliminate artifacts while preserving detector sensitivity.
Solution Approach 2:
The patent implements feedback by continuously measuring detector response characteristics and using these measurements to update correction parameters. The system monitors actual detector behavior and adjusts the correction algorithm accordingly, creating a closed-loop system that compensates for lag effects while maintaining sensitivity.
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
This approach effectively reduces artifacts in images by accurately accounting for trap states, resulting in corrected projection data with minimal lag and gain changes, improving the quality of reconstructed images.
Implementation Method 1
Radiation (e.g., alpha, beta, gamma, X-ray, neutrons, protons, heavy ions, etc.) strikes the scintillator and causes the scintillator to generate visible light.
Implementation Method 2
The visible light strikes a photodiode and generates an electric current.
Implementation Method 3
The current charges a capacitor and leaves a charge on the capacitor. The integrated charge on the capacitor is proportional to the integrated light intensity striking the respective photoconductor for a given integration time.
Data Source
Figure 1A
Figure 1B
Figure 2
AI summary
A method is described. A total number of traps to be filled in a detector of an imaging system is estimated based on a measured signal sensed by the detector. The measured signal is adjusted based on the estimated total number of traps and a current trap state of the detector. The trap state of the detector is subsequently updated.