CT Gantry Movement Correction via Image Processing
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Solution Overview
Problem
Compact and mobile computed tomography devices face instability in the movement of their gantry, which affects the accuracy of three-dimensional image reconstruction, necessitating a method to ensure stability and accuracy of the reconstructed images despite involuntary patient movement and unstable gantry trajectories.
Innovation Solution
A computed tomography device with a gantry, detector, and arm system that uses an image processing processor to generate initial and corrected transformation projection matrices, allowing for stable three-dimensional reconstruction by accounting for gantry movement and patient movement through back projection and correction processes, operating in either rigid or non-rigid body transformation modes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a compact and mobile computed tomography device is used, then cost and mobility are improved, but gantry movement stability deteriorates
Solution Approach 1:
The system uses detected marker positions to calculate transformation projection matrices that correct for gantry movement deviations. The detected positions feed back into the image reconstruction process to compensate for instability, allowing compact devices to achieve accurate images despite movement variations.
Solution Approach 2:
The system dynamically adjusts transformation parameters (translation and rotation values) based on detected marker positions. By changing these parameters according to actual gantry position deviations, the system compensates for movement instability and maintains image reconstruction accuracy.
2Ease of operation
If a compact and mobile computed tomography device is used, then patient convenience is improved, but image reconstruction accuracy deteriorates
Solution Approach 1:
Markers serve as intermediary reference objects between the gantry and the subject. By detecting marker positions and using them to calculate correction matrices, the system indirectly compensates for both gantry movement and subject movement, maintaining image accuracy in mobile applications.
Solution Approach 2:
The system replaces mechanical precision requirements with computational correction. Instead of relying on mechanically precise gantry movement, the system uses image processing and transformation matrices to achieve accurate reconstruction, enabling mobile devices to maintain diagnostic quality.
3Measurement precision
If conventional fixed large computed tomography device is used, then image reconstruction accuracy is improved, but device complexity and cost increase
Solution Approach 1:
The system extracts the essential reference information needed for accurate reconstruction by using only markers and their detected positions. This separates the critical measurement function from the complex mechanical system, allowing accurate imaging with simpler mobile devices.
4Reliability
If transformation projection matrix correction is applied, then image reconstruction stability is improved, but processing complexity increases
Solution Approach 1:
The system performs preliminary detection of marker positions and calculates transformation matrices before final image reconstruction. By preparing correction data in advance, the actual reconstruction process becomes more stable and efficient, as the correction parameters are already determined.
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 solution enables the generation of stable three-dimensional reconstruction images even with unstable gantry movement and patient movement, improving the accuracy and reliability of computed tomography imaging in compact and mobile devices.
Implementation Method 1
A computed tomography device extracts a plurality of two-dimensional images while an X-ray light source rotates around a subject
Data Source
AI summary
Provided are a computed tomography device and a computed tomography method. The computed tomography device includes a gantry and an image processing processor. The gantry includes a light source for irradiating light, a detector disposed facing the light source and for receiving the light, and an arm for supporting the light source and the detector. The image processing processor receives a two-dimensional detection image for a subject from the detector. The image processing processor converts the received two-dimensional detection image to two-dimensional detection image data. The image processing processor generates three-dimensional reconstruction image data from the two-dimensional detection image data. A computed tomography device and a computed tomography method according to the inventive concept correct an error of a gantry movement path to provide a stable three-dimensional reconstruction image.