Adaptive Medical Imaging Motion Correction
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Solution Overview
Problem
Patient motion during medical data acquisition in systems like MRI and PET leads to image artifacts, increased diagnosis time, and costs, as existing techniques often detect motion too late and lack comprehensive correction capabilities.
Innovation Solution
A method and system for early detection and classification of patient motion, allowing for automatic adaptation of the data acquisition strategy by using object motion data to categorize data as tolerable or intolerable, and adjusting the acquisition parameters accordingly, such as changing the k-space sampling scheme or using motion correction techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If patient motion is detected using existing techniques (monitoring camera, artifact analysis), then motion can be identified, but detection occurs too late (after data acquisition or during post-processing)
Solution Approach 1:
The patent applies preliminary action by performing motion detection and classification during the data acquisition process itself, rather than after acquisition. The system continuously monitors patient motion and classifies it as tolerable or intolerable in real-time, enabling early detection and immediate response before motion artifacts corrupt the medical data.
2Manufacturing precision
If data acquisition is stopped and restarted due to detected motion, then image quality can be maintained, but total examination time increases significantly
Solution Approach 1:
The patent applies dynamics by implementing an adaptive data acquisition strategy that dynamically adjusts the acquisition process based on real-time motion classification. When motion is classified as tolerable, acquisition continues without interruption; when intolerable motion is detected, acquisition is paused and resumed with adjusted parameters. This dynamic adaptation maintains image quality while minimizing examination time by avoiding unnecessary stops.
Solution Approach 2:
The system changes acquisition parameters adaptively based on motion classification. When motion is detected and classified as intolerable, the system modifies acquisition parameters (such as pausing, resuming, or adjusting sampling rates) to maintain image quality while reducing the impact on total examination time compared to complete restarts.
3Loss of time
If operator manually monitors patient motion continuously, then motion can be detected early, but operator attention is required and visual field is limited
Solution Approach 1:
The patent applies self-service by implementing an automated motion detection and classification system that operates independently without requiring continuous operator intervention. The system autonomously monitors patient motion, classifies it as tolerable or intolerable, and adapts the data acquisition strategy automatically, freeing the operator from continuous monitoring while maintaining early detection capabilities.
Solution Approach 2:
The system replaces the mechanical/visual monitoring approach with an automated electronic detection and classification system. Instead of relying on operator visual inspection through monitoring cameras, the system uses automated sensors and algorithms to detect and classify motion, eliminating the limitations of human attention and visual field while reducing operator workload.
4Manufacturing precision
If motion correction techniques are applied retrospectively, then some motion artifacts can be corrected, but the techniques have limitations on maximum correctable motion
Solution Approach 1:
The patent applies preliminary action by classifying motion as tolerable or intolerable during acquisition, enabling proactive rather than reactive correction. By identifying intolerable motion before it severely degrades data quality, the system can pause acquisition and prevent further corruption, whereas retrospective techniques must work with already degraded data, limiting their effectiveness for severe motions.
Data Source
AI summary
A method for adapting a medical system to an object movement during medical examination of the object and a medical system configured for carrying out the method. The medical system has a device for detecting and quantifying a motion of the object before or during an acquisition of diagnostic data. The system for detecting and quantifying a motion of the object is able to directly identify and qualify the occurrence of object motion and to automatically suggest an adaptation of the diagnostic data acquisition strategy/technique as a function of the object motion.