CT Geometric Parameter Calibration via Marker Image Analysis
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Solution Overview
Problem
Current CT imaging machines face challenges in accurately determining geometric parameters such as source-to-imager distance, source-to-axis distance, axis of rotation, and piercing point due to slippage and strain between machine components, making manual measurement inconvenient and difficult, especially at multiple gantry rotational angles.
Innovation Solution
A system and method using a calibration device with markers positioned between the radiation source and detector, generating images at various gantry angles to determine geometric parameters through image processing, including background subtraction and marker position correlation, allowing for automatic calculation of these parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual measurement methods are used to determine geometric parameters, then measurement precision can be maintained, but ease of operation deteriorates due to the difficulty and inconvenience of manually obtaining parameters at multiple gantry rotational angles
Solution Approach 1:
The patent replaces manual mechanical measurement methods with an automated image processing system. A calibration device with markers is imaged by the CT system, and software automatically determines geometric parameters by analyzing marker positions in the images, eliminating the need for manual physical measurement while maintaining or improving accuracy.
Solution Approach 2:
The system enables self-calibration by using the CT system's own imaging capability to capture marker positions. The geometric parameters are automatically calculated from the captured images without requiring external measurement tools or manual intervention, allowing the system to determine its own parameters autonomously.
2Reliability
If the CT imaging machine is made as rigid as possible with active control mechanisms, then reliability of geometric parameters is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex mechanical rigidity and active control mechanisms with a software-based solution. Instead of relying on purely mechanical stability, the system uses image processing algorithms to automatically detect and compensate for positional variations of markers, thereby determining accurate geometric parameters without requiring the machine to be perfectly rigid.
Solution Approach 2:
The system changes from maintaining fixed mechanical parameters to dynamically determining parameters through image analysis. By capturing images at multiple gantry angles and analyzing marker positions, the system can adaptively determine geometric parameters that account for actual machine positions, rather than relying on predetermined mechanical specifications.
3Productivity
If automated image processing methods are used to determine geometric parameters, then productivity is improved through automatic calculation, but measurement precision may deteriorate due to potential errors in image processing
Solution Approach 1:
The patent introduces a calibration device with high-precision markers as an intermediary standard. These markers serve as a reference framework that bridges the gap between the physical machine geometry and the digital image data. By tracking marker positions accurately, the system can reliably determine geometric parameters through automated processing without sacrificing precision.
Solution Approach 2:
The system uses feedback from the captured images to iteratively refine the determination of geometric parameters. The marker positions detected in the images provide feedback that allows the software to calculate and verify parameter accuracy, enabling automatic adjustment and validation to ensure precision while maintaining high productivity.
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
Enables accurate and efficient determination of geometric parameters without manual intervention, reducing errors and improving the precision of CT image reconstruction and diagnostic accuracy.
Implementation Method 1
The x-ray source generates and directs an x-ray beam towards the patient
Implementation Method 2
the detector apparatus measures the x-ray absorption at a plurality of transmission paths defined by the x-ray beam
Data Source
AI summary
A method of determining a geometric parameter of a machine includes using the machine to obtain an image of at least a portion of a structure, the structure having a plurality of markers, wherein the markers have predetermined position(s) relative to each other, determining a position of the structure based on a pattern of the markers in the image, and determining a geometric parameter of the machine based at least in part on the determined position of the structure.