Motion Detection in Dynamic Medical Images via Composite Signal Analysis
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Solution Overview
Problem
Current medical imaging techniques face challenges in detecting and correcting patient motion during long scan times, which affects the quality of image data and requires computationally intensive methods that are time-consuming and often require user intervention, especially when contrast agents are used.
Innovation Solution
An automated system and method for detecting patient motion by identifying a region of interest, determining signal characteristics, generating a composite signal, and analyzing it to detect and correct motion, which can enhance clinical workflow and image data quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If feature-based methods or registration methods are used for detecting patient motion, then motion detection capability is improved, but computational complexity and time consumption increase significantly
Solution Approach 1:
The patent extracts only the necessary signal characteristics (magnitude and phase) from the MRI data that are sufficient for motion detection, rather than performing complete image reconstruction or complex feature analysis. This selective extraction reduces computational burden while maintaining motion detection accuracy
Solution Approach 2:
The motion detection process is segmented into distinct steps: acquiring raw k-space data, computing signal characteristics, generating composite signals, and detecting motion. This segmentation allows each step to be optimized independently and reduces overall computational complexity compared to holistic image-based methods
2Measurement precision
If feature-based methods or registration methods are used for detecting patient motion, then motion detection capability is improved, but time consumption increases
Solution Approach 1:
The patent performs motion detection during the image acquisition process itself by analyzing signal characteristics in k-space before complete image reconstruction. This preliminary detection allows for real-time or near-real-time motion identification without adding post-processing time
Solution Approach 2:
Only the essential signal characteristics needed for motion detection are extracted and analyzed, avoiding time-consuming complete image reconstruction and complex feature analysis. This selective approach significantly reduces processing time while maintaining detection accuracy
3Manufacturing precision
If contrast agent is used for dynamic contrast enhanced MRI, then image quality for perfusion analysis is improved, but motion detection becomes more difficult
Solution Approach 1:
The patent analyzes signal characteristics in specific regions of interest where motion effects are most prominent, rather than attempting to analyze the entire image. This localized approach allows motion detection to proceed effectively even in the presence of contrast agent-induced signal variations in other regions
Solution Approach 2:
The patent uses composite signals generated from multiple signal characteristics as an intermediary representation that separates motion information from contrast agent information. This intermediary representation allows motion detection to proceed independently of contrast agent effects
Data Source
AI summary
A system and method for detecting motion is presented. The system and method includes identifying a region of interest in the plurality of images corresponding to a subject of interest. Furthermore, the system and method includes determining signal characteristics corresponding to the region of interest. In addition, the system and method includes generating a composite signal, where the composite signal comprises an aggregate of the signal characteristics corresponding to the region of interest. The system and method also includes analyzing the composite signal to detect motion in the region of interest.