X-Ray Image Selection for Accurate 3D Device Position Detection
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Solution Overview
Problem
Existing X-ray imaging systems struggle to accurately determine the three-dimensional position of a treatment device during interventional procedures due to the influence of aperiodic body motions, such as physiological reflexes, which can degrade the accuracy of position calculation even when using techniques that account for periodic motions like respiratory motion.
Innovation Solution
An X-ray imaging apparatus and method that analyzes a combination of X-ray images with minimal body motion influence by classifying movements of feature points, selecting X-ray images based on motion type, and calculating the three-dimensional position using a combination of images with the least body motion impact.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple X-ray images are used to calculate three-dimensional device position, then position detection accuracy is improved, but the influence of body motion (especially aperiodic motion) increases and degrades calculation accuracy
Solution Approach 1:
The system performs preliminary classification of body motion types (periodic vs. aperiodic) before selecting images for three-dimensional position calculation. By analyzing movement vectors of feature points in advance, the system identifies and excludes images contaminated by aperiodic motion, ensuring that only suitable images are used for accurate position calculation.
Solution Approach 2:
The system calculates movement vectors of feature points from multiple X-ray images and uses this feedback information to classify body motion types. Based on this classification, it selectively combines images that minimize body motion influence, creating a feedback loop that continuously optimizes position calculation accuracy despite ongoing patient motion.
2Loss of information
If X-ray images are acquired at different imaging positions to enable three-dimensional position calculation, then device position information is improved, but acquisition time increases
Solution Approach 1:
Instead of using all acquired X-ray images for three-dimensional position calculation, the system selectively uses only those images that are not influenced by aperiodic body motion. This partial action approach avoids the time loss associated with processing unnecessary images while still obtaining sufficient information for accurate position determination.
3Measurement precision
If cone beam CT is used to acquire three-dimensional images, then three-dimensional device position can be identified, but acquisition time increases and positional accuracy decreases during subject motion
Solution Approach 1:
The system extracts only the necessary information (device position) from multiple two-dimensional X-ray images by classifying and selecting images based on body motion characteristics. This extraction approach avoids the time-consuming full three-dimensional reconstruction of cone beam CT while achieving accurate device position identification without being affected by subject motion during extended acquisition periods.
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 enables highly accurate three-dimensional position detection of devices during interventional procedures by minimizing the influence of aperiodic body motions, ensuring precise device positioning even in the presence of unexpected movements.
Implementation Method 1
an X-ray source that emits X-rays, and an X-ray detector disposed to face the X-ray source with an examination target interposed therebetween, the imaging unit being configured to generate an X-ray image of the examination target based on X-rays transmitted through the examination target and detected by the X-ray detector
Data Source
Figure 1
Figure 2A~2B
Figure 3A~3B
AI summary
Provided is a technique capable of reducing an influence of aperiodic motion that has occurred during interventional imaging and of monitoring a three-dimensional position of a device with high accuracy. In order to monitor a device position in interventional imaging, a combination of X-ray images with a minimum influence of body motion is obtained from a plurality of X-ray images acquired at different imaging positions, and the device position is calculated. In this case, movements of feature points extracted from the plurality of X-ray images are analyzed to classify a movement of body motion that has occurred during imaging, a combination of X-ray images to be used for calculating the device position is selected based on classification results, and the device position is calculated.