Constrained-Curve Correlation Model for Non-Linear Target Tracking
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Solution Overview
Problem
Conventional radiation treatment systems fail to accurately track the non-linear movement of internal targets during respiratory and other patient motions, as they rely on linear modeling and manual image acquisition, leading to inconsistent distribution of model points and increased unnecessary imaging.
Innovation Solution
A method and system that utilize a parameterization function with a constrained curve to approximate non-linear target movement, requiring only one sample point for correlation model development, and include a shrinking algorithm to adapt to changes in movement behavior, reducing the need for multiple images and improving tracking accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional linear modeling is used to track internal organ movement, then the model development process is simple, but the tracking accuracy for non-linear multi-path movements is insufficient
Solution Approach 1:
The patent applies curvilinear modeling to represent the non-linear paths of internal organ movement during respiration. Instead of using straight-line linear models, the system employs curved trajectories that accurately follow the actual multi-path movement patterns of organs during inspiration and expiration, thereby improving tracking accuracy for non-linear movements
Solution Approach 2:
The patent segments the respiratory cycle into distinct phases (inspiration and expiration) and models each phase with separate curvilinear paths. This segmentation allows the system to capture the different movement trajectories during inhalation and exhalation, improving the overall accuracy of non-linear movement tracking
2Manufacturing precision
If manual triggering of imaging system is used to acquire model points, then the operator has control over image acquisition, but the distribution of model points is inconsistent and additional images are needed
Solution Approach 1:
The patent implements an automated feedback mechanism where the imaging system is triggered based on real-time detection of respiratory phase. The system monitors respiratory motion and automatically activates the imaging system at appropriate phases, ensuring consistent distribution of model points without requiring manual operator intervention or additional corrective images
Solution Approach 2:
The patent replaces the manual mechanical triggering system with an automated sensor-based triggering system. The automated system uses respiratory motion detection to trigger image acquisition, eliminating the inconsistencies introduced by manual operation and improving imaging efficiency by reducing unnecessary images
3Measurement precision
If multiple images are acquired to overcome uneven distribution of model points, then the model point coverage is improved, but the number of unnecessary imaging occurrences increases
Solution Approach 1:
The patent performs preliminary action by pre-planning the image acquisition strategy based on the respiratory cycle phases. The system determines in advance which phases require imaging and triggers acquisitions only at those predetermined optimal moments, ensuring adequate model point coverage while avoiding unnecessary images and reducing imaging resource waste
Data Source
AI summary
A method and apparatus to develop an advanced correlation model of movement of a target within a patient, which needs less data points and can adapt to the changes of respiration behavior automatically.