Color Flow Ultrasound Vessel Identification for Faster Doppler Measurement
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Solution Overview
Problem
Existing ultrasound imaging systems require manual identification and adjustment of pulsed wave cursors for arteries and veins, leading to potential errors and increased time consumption, especially when fine angle adjustments are necessary.
Innovation Solution
The system automatically identifies arteries and veins in a color flow image and adjusts imaging parameters such as steering angle and Doppler angle, using methods like detecting aliasing, flow direction, and pulsatility to accurately position the pulsed wave cursor.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual identification and adjustment of pulsed wave cursors is used for arteries and veins, then the system requires user input and control, but this leads to potential errors and increased time consumption
Solution Approach 1:
The system automatically identifies vessels and adjusts imaging parameters without requiring manual user input. The processor autonomously performs vessel identification, cursor positioning, and parameter optimization, eliminating the time-consuming manual adjustment process while maintaining measurement accuracy through automated algorithms
Solution Approach 2:
The system performs preliminary automatic identification of vessels and pre-positioning of cursors before measurement begins. By automatically detecting vessel characteristics and pre-adjusting imaging parameters in advance, the system eliminates the need for time-consuming manual adjustments during the measurement process
2Ease of operation
If manual adjustment of pulsed wave cursors is performed, then user control is maintained, but fine angle adjustments become time consuming
Solution Approach 1:
The system automatically performs fine angle adjustments by detecting vessel orientation and autonomously optimizing the Doppler angle. The processor analyzes vessel geometry and automatically positions the pulsed wave cursor at the optimal angle, eliminating the need for manual fine-tuning while maintaining measurement accuracy
Solution Approach 2:
The system replaces manual mechanical adjustment of imaging parameters with automated computational methods. The processor uses image analysis algorithms to automatically determine optimal cursor positioning and angle settings, substituting manual mechanical adjustment with automated digital processing
3Reliability
If manual identification of vessels is performed, then user expertise is utilized, but errors may occur and time is increased
Solution Approach 1:
The system automatically identifies vessels and performs measurements without requiring repeated manual intervention. The automated identification algorithm consistently recognizes vessel structures and maintains measurement consistency across multiple measurements, eliminating human error while reducing measurement time
Solution Approach 2:
The system uses feedback from image analysis to automatically adjust and refine vessel identification and measurement parameters. By continuously analyzing image data and adjusting parameters based on detected vessel characteristics, the system maintains high measurement consistency and accuracy without manual intervention
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
This approach enhances measurement accuracy and reduces user input, minimizing errors and time required for blood flow measurements in ultrasound imaging.
Implementation Method 1
in a color flow imaging mode, the Doppler effect is used to detect the presence of blood flow in the body. Flow velocities in a given location in a vessel can be estimated using the measured Doppler shift
Data Source
AI summary
Various methods and systems for color flow ultrasound imaging of arteries and veins are provided. In one embodiment, a method comprises acquiring a color flow image, automatically identifying an artery and a vein within the color flow image, and adjusting at least one imaging parameter responsive to the automatic identification of the artery and the vein. In this way, flow velocities and volume flow in arteries and veins may be measured with minimal adjustments or input by a user, thereby increasing the accuracy and consistency of measurements and reducing the time needed for blood flow measurements.