CT Scan Data Restoration via Detector Response Modeling
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Solution Overview
Problem
In Computed Tomography (CT) scanning, the limited physical size and sensitivity of detectors result in insufficient CT scan data, leading to distorted CT images due to the need for interpolation, which compromises image clarity.
Innovation Solution
A method is introduced to restore CT scan data using a data collecting model based on the response curve of detectors, ensuring the restored data aligns with the original data model, thereby reducing distortion and improving image accuracy. This involves building a data collecting model for specific directions, determining functions that satisfy continuity and boundary conditions, and calculating X-ray intensity values to reconstruct CT images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the physical size of detectors is increased to capture more CT scan data, then the amount of CT scan data increases, but the device complexity and manufacturing difficulty increase
Solution Approach 1:
The patent transitions from physical expansion of detectors to mathematical dimensionality by introducing a data collecting model with response curves that operate in parameter space rather than physical space. The model uses continuous functions to represent detector responses across multiple dimensions (energy, angle, position) allowing virtual expansion of data collection capability without physical detector expansion.
Solution Approach 2:
The patent changes the parameters of data representation by introducing response curve models that describe detector behavior in terms of continuous functions. Instead of adding more physical detectors, the system modifies the parameter space by incorporating energy-dependent response curves, angular response characteristics, and position-dependent sensitivity profiles into the data collection model.
2Area of stationary object
If interpolation is used to restore CT scan data, then image coverage is improved, but image clarity and accuracy deteriorate due to data distortion
Solution Approach 1:
The patent applies preliminary action by establishing a data collecting model with response curves before actual image reconstruction occurs. The model pre-characterizes detector behavior and establishes continuous functions that describe the relationship between measured signals and actual X-ray attenuation, allowing accurate data restoration without relying on post-hoc interpolation that distorts image data.
Solution Approach 2:
The patent introduces a data collecting model with response curves as an intermediary between raw detector signals and reconstructed images. This intermediate layer processes and corrects detector responses using continuous functions that account for energy dependence, angular variation, and position effects, thereby eliminating the need for distortion-causing interpolation while maintaining accurate image reconstruction.
3Quantity of substance
If more detectors are added to improve data collection, then the amount of CT scan data increases, but the device complexity and cost increase
Solution Approach 1:
The patent creates a mathematical copy of the detector system through response curve models that replicate detector behavior without requiring physical detector copies. The continuous functions serve as virtual replicas that capture the essential characteristics of detector responses across different energies, angles, and positions, enabling comprehensive data collection modeling without proportional increases in physical hardware.
Solution Approach 2:
The patent achieves multi-functionality by designing a universal data collecting model with response curves that can characterize any detector in the array using the same mathematical framework. The continuous functions serve multiple purposes simultaneously: modeling energy dependence, angular response, position sensitivity, and interpolation behavior, thereby replacing multiple specialized detector components with a single versatile mathematical model.
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 method ensures that the restored CT scan data is consistent with the original data model, reducing distortion and enhancing the accuracy of reconstructed CT images, thereby improving image clarity.
Implementation Method 1
a series of X-ray attenuation data (hereinafter referred as 'CT scan data') may be generated and CT scan data captured by detectors
Data Source
AI summary
A method for restoring CT scan data is disclosed. The method may comprise: building a data collecting model with respect to a specific direction of a detector based a response curve of the detector. In some examples, the specific direction can indicate a channel direction and a slice direction of the detector. During a CT scanning, based on the data collecting model, X-ray intensity values detected by the detectors in the specific direction can be acquired. A function can be determined such that it satisfies the data collecting model, a continuity condition and a boundary condition, An X-ray intensity value can be obtained by substituting the coordinate value of a point in the specific direction into the function.