Ultrasound Controller Detecting Probe Drift via Anatomical Feature Tracking
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Solution Overview
Problem
Long-term cardiac ultrasound monitoring faces challenges due to probe displacement, leading to drifting of the field of view, which reduces image quality and requires frequent operator intervention, causing disruptions and data gaps.
Innovation Solution
An ultrasound processing unit that monitors the movement of anatomical features within the field of view, providing early alerts to operators about potential drift, allowing for timely adjustments before the feature moves outside the view, using real-time ultrasound data and image segmentation techniques to estimate the remaining time before misalignment occurs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the operator manually checks the field of view frequently to detect probe displacement, then the reliability of monitoring is improved, but the productivity is worsened due to operator time loss and disruptions
Solution Approach 1:
The system performs self-monitoring by automatically detecting probe displacement through anatomical feature tracking, eliminating the need for operator intervention. The processing unit continuously analyzes ultrasound data to detect field of view drift and generates alerts autonomously, allowing the system to serve itself in monitoring its own operational status.
Solution Approach 2:
The system implements automatic feedback by continuously monitoring anatomical feature positions and providing real-time alerts when displacement is detected. This closed-loop feedback mechanism enables the system to detect and communicate probe misalignment issues without operator intervention, improving both reliability and productivity.
2Device complexity
If the operator waits for the alarm to sound before adjusting the probe, then the device complexity is reduced, but the loss of time increases due to gaps in monitoring data
Solution Approach 1:
The system performs preliminary detection by continuously tracking anatomical feature positions and identifying drift trends before the feature moves completely out of view. By detecting displacement early and providing advance alerts, the system enables operators to adjust the probe proactively, preventing data gaps before they occur.
Solution Approach 2:
The system dynamically adjusts its monitoring approach by providing graduated alerts based on the severity and progression of probe displacement. Rather than a single threshold-based alarm, the system can provide early warnings for gradual drift and critical alerts for severe misalignment, enabling timely intervention at multiple stages.
3Reliability
If the system uses anatomical feature tracking to detect drift early, then the reliability is improved, but the device complexity increases due to additional processing requirements
Solution Approach 1:
The system extracts only the essential information needed for drift detection by tracking specific anatomical feature positions rather than analyzing entire images. By focusing on key landmarks and their spatial relationships, the system reduces processing complexity while maintaining high reliability in detecting probe displacement.
Solution Approach 2:
The system segments the ultrasound image analysis task by first identifying anatomical features through model-based segmentation, then separately tracking their positions over time. This segmentation of the processing pipeline allows for efficient, specialized algorithms for each task, reducing overall system complexity while improving detection reliability.
Data Source
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AI summary
The invention provides an ultrasound processing unit. A controller (18) of the unit is adapted to receive ultrasound data of an anatomical region, for example of the heart. The controller processes the ultrasound data over a period of time to monitor and detect whether alignment of a particular anatomical feature (34) represented in the data relative to a field of view (36) of the transducer unit is changing over time. In the event that the alignment is changing, the controller generates an output signal for communicating this to a user, allowing a user to be alerted at an early stage to likelihood of misalignment and loss of imaging or measurement capability.