Event-Driven Ultrasound Sampling for Power and Data Reduction
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Solution Overview
Problem
Current ultrasound imaging systems face challenges in providing consistent and accurate images due to dynamic movements within the body, leading to limited image quality and resource constraints, particularly in catheter-based applications where high data rates and power consumption are issues.
Innovation Solution
The implementation of event-driven sampling algorithms that reduce the average sampling rate by only sampling meaningful data changes, optimizing resource usage and minimizing power consumption, while maintaining clinically relevant image quality through adaptive sampling thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous high-rate sampling is used to capture dynamic body movements, then image quality and diagnostic accuracy are improved, but power consumption and data transmission requirements increase significantly
Solution Approach 1:
The system dynamically adjusts the sampling rate based on detected motion events. When motion is detected above a threshold, the sampling rate increases to capture relevant changes; when motion is minimal, the sampling rate decreases to conserve power. This dynamic adaptation resolves the contradiction between maintaining image quality and reducing power consumption.
Solution Approach 2:
The system changes the sampling rate parameter in response to detected events. By monitoring for changes in the ultrasound signal and adjusting the sampling frequency accordingly, the system maintains diagnostic accuracy when needed while reducing power consumption during stable periods.
2Loss of information
If high sampling rate is maintained to capture all data changes, then complete information is captured, but data transmission rate and resource requirements increase
Solution Approach 1:
The system extracts only the meaningful portions of the ultrasound signal by detecting events where actual changes occur. Instead of transmitting all sampled data, only data associated with detected events is transmitted, thereby maintaining information completeness for diagnostic purposes while significantly reducing the overall data transmission rate.
Solution Approach 2:
The system performs partial sampling by capturing data only when events are detected rather than continuous sampling. This partial action approach maintains sufficient information for diagnosis while reducing the total volume of data that needs to be transmitted and processed.
3Measurement precision
If sampling threshold is set low to capture all changes, then all data variations are recorded, but noise and irrelevant data increase
Solution Approach 1:
The system uses adaptive thresholding where the sampling threshold is dynamically adjusted based on the characteristics of the ultrasound signal and detected event patterns. This parameter change allows the system to distinguish between meaningful diagnostic information and noise, maintaining data accuracy while filtering out irrelevant variations.
4Use of energy by moving object
If low sampling rate is used to conserve resources, then power consumption is reduced, but image quality and diagnostic capability deteriorate
Solution Approach 1:
The system dynamically switches between low and high sampling rates based on detected events. During periods of minimal change, low sampling rate conserves power; when events are detected indicating potential diagnostic relevance, the sampling rate increases to maintain image quality. This dynamic approach resolves the contradiction between power consumption and image quality.
Data Source
AI summary
The invention generally relates to ultrasound imaging, and, more particularly, to systems and methods for providing event-driven ultrasound imaging.