Interventional X-Ray Image Pairing for Aperiodic Motion-Robust 3D Tracking
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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 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 periodic or aperiodic motion types, and calculating the three-dimensional position using a combination of images with minimal body motion impact.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If multiple X-ray images are acquired at different imaging positions to calculate three-dimensional device position, then position detection capability is improved, but measurement precision deteriorates due to body motion during imaging
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 images captured during aperiodic motion and excludes them from calculation, thereby preventing motion-induced accuracy deterioration while maintaining the ability to detect device position from multiple imaging positions
Solution Approach 2:
The system calculates movement vectors of feature points between consecutive X-ray images and uses this feedback information to classify body motion types. This feedback mechanism enables real-time identification of images affected by aperiodic motion, allowing the system to dynamically select only those images with minimal motion influence for three-dimensional position reconstruction, thus resolving the contradiction between using multiple images and maintaining precision
2Productivity
If X-ray images are acquired continuously during interventional procedures, then productivity is improved, but reliability deteriorates due to aperiodic body motions such as physiological reflexes
Solution Approach 1:
The system extracts and analyzes movement vectors of feature points from continuously acquired X-ray images to identify aperiodic motion events. By separating images captured during aperiodic motion from those captured during stable conditions, the system excludes unreliable images from three-dimensional position calculation. This extraction approach allows continuous imaging for high productivity while maintaining reliability by using only stable images for measurement
Solution Approach 2:
Before performing three-dimensional position calculation, the system preliminarily classifies each acquired image based on body motion stability by analyzing feature point movements. This preliminary classification ensures that only images with minimal aperiodic motion influence are selected for position reconstruction, maintaining calculation reliability even during continuous imaging procedures where aperiodic motions may occur
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
Data Source
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.