Respiratory Extrema Prediction for Low-Latency CT Gating
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Solution Overview
Problem
Existing respiratory monitoring devices often provide poor-quality or no gating signals, leading to inaccurate respiratory gated CT scans due to respiratory motion artifacts, which hinder accurate imaging of lung structures and radiotherapy treatments.
Innovation Solution
A CT system generates its own respiratory gating signals based on predicted extrema of respiratory motion using a Kalman filter and adaptive learning algorithms, integrating with real-time respiratory waveforms to ensure accurate and timely image capture at respiratory cycle extrema.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing respiratory monitoring devices are used to generate gating signals, then the system is simple to operate, but the gating signal quality is poor leading to inaccurate CT scans
Solution Approach 1:
The CT system generates its own respiratory gating signals using internally acquired respiratory waveforms and extrema detection algorithms, eliminating dependence on external respiratory monitoring devices and their associated signal quality issues
Solution Approach 2:
The patent replaces traditional mechanical/respiratory monitoring device-based gating signal generation with a computational approach using Kalman filters and adaptive learning algorithms to detect respiratory extrema from CT-acquired waveforms
2Measurement precision
If respiratory gating is used to reduce motion artifacts, then image accuracy improves, but the system requires complex gating signal processing
Solution Approach 1:
The system uses adaptive learning algorithms that continuously learn from acquired respiratory waveforms and adjust extrema detection parameters in real-time, creating a feedback mechanism that improves gating signal quality while maintaining operational simplicity
Solution Approach 2:
The Kalman filter predicts future respiratory extrema positions based on current waveform data, allowing the system to prepare gating signals in advance of actual respiratory events, improving timing accuracy without increasing processing complexity
3Measurement precision
If traditional extrema detection methods are used, then the system is computationally simple, but detection accuracy and timing precision are insufficient
Solution Approach 1:
The Kalman filter performs preliminary prediction of respiratory extrema positions and timing before actual detection is needed, pre-computing trajectory information that simplifies subsequent extrema identification and reduces real-time computational burden
4Speed
If real-time respiratory waveform monitoring is implemented, then gating signal timing improves, but latency in extrema detection increases
Solution Approach 1:
The system continuously maintains a predicted trajectory of respiratory extrema using the Kalman filter during the entire data acquisition process, so when an extremum occurs, the system can immediately identify it against the pre-computed trajectory without requiring post-processing analysis, eliminating detection latency
Data Source
AI summary
Prediction of extrema in respiratory motion and related systems, methods, and devices is disclosed. A method of detecting extrema in respiratory motion includes generating a predicted motion trajectory of respiratory motion, identifying one or more extrema candidates of the motion of the patient responsive to the predicted motion trajectory, and selecting one or more of the one or more extrema candidates to be one or more predicted extrema of the respiratory motion of the patient. An apparatus includes an input terminal configured to receive a respiratory waveform signal and one or more processors configured to generate predictions of extrema of the respiratory waveform signal before occurrences of the extrema. An imaging system includes a gating signal generator configured to predict extrema of a respiratory waveform and an imaging device configured to capture images of a patient responsive to a respiratory gating signal from the gating signal generator.