FMCW Radar Motion Detection for Medical Imaging Artifact Reduction
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Solution Overview
Problem
Medical imaging systems, such as CT and MRI scanners, face challenges in accurately detecting and localizing lesions due to subject motion during scans, which results in motion artifacts in the images.
Innovation Solution
A method and system for motion detection using a computing device with a processor and storage, employing a frequency modulated continuous wave (FMCW) radar to obtain detection data from a subject within the field of view of a medical device, determining motion data such as posture and physiological motion, and generating control signals to improve image quality by correcting artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a subject remains still during a medical scan, then image quality is improved, but it is difficult to maintain stillness due to posture motion and physiological motion
Solution Approach 1:
The system performs preliminary motion detection and analysis before the scan begins, establishing baseline motion patterns and predicting future motion. This allows the scanning process to be pre-coordinated with expected motion states, enabling artifact correction to be applied proactively rather than reactively
Solution Approach 2:
The system continuously monitors subject motion during scanning using detection devices, feeds this motion information back to the control system, and dynamically adjusts scanning parameters or applies correction algorithms in real-time to compensate for detected motion and maintain image quality
2Manufacturing precision
If motion detection and correction systems are added to medical imaging devices, then image quality is improved, but device complexity increases
Solution Approach 1:
The detection devices are designed to serve multiple functions: they detect posture motion, physiological motion (respiratory and cardiac), and provide timing information for gating. This multi-functionality reduces the need for separate specialized devices and integrates motion management into the existing scanning system
Solution Approach 2:
The control system acts as an intermediary that receives motion data from detection devices, processes this information, and translates it into corrected scanning commands or artifact correction parameters. This intermediary layer simplifies the integration by providing a standardized interface between motion detection and image reconstruction subsystems
3Measurement precision
If multiple detection devices are used to monitor the subject, then motion detection accuracy is improved, but the quantity of detection data increases
Solution Approach 1:
The system extracts and processes only the essential motion parameters from the detection data, such as position, velocity, and key physiological markers. By extracting only the relevant features needed for motion correction rather than processing all raw detection data, the system maintains accuracy while reducing data volume
Solution Approach 2:
The detection data processing is segmented into separate analysis streams for different motion types (posture motion, respiratory motion, cardiac motion). Each stream processes specific parameters relevant to that motion type independently, then integrates results for comprehensive correction. This segmentation reduces overall processing complexity and data volume
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
The system effectively reduces motion artifacts in medical images by accurately detecting subject motion and enabling controlled scanning, thereby enhancing the accuracy of lesion detection and localization.
Implementation Method 1
employing a frequency modulated continuous wave (FMCW) radar to obtain detection data from a subject
Data Source
AI summary
The present disclosure is related to systems and methods for motion detection. The method includes obtaining, via at least one detection device, detection data of a subject located in a field of view (FOV) of a medical device. The method also includes determining motion data of the subject based on the detection data.