Doppler Ultrasound Vessel Identification for Artery-Vein Classification
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Solution Overview
Problem
Accurate and reliable identification of blood vessels, such as arteries and veins, is challenging for untrained operators in ultrasound imaging, particularly in environments like OR/ICU where live image feedback is not available, leading to incorrect placement of ultrasound probes.
Innovation Solution
A computer-implemented method using Doppler ultrasound data to identify vessels as arteries or veins based on flow characteristics, employing feature extraction algorithms and machine learning to analyze frequency envelopes and color distribution, with guidance for probe placement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional ultrasound imaging with live image feedback is used, then vessel identification accuracy is improved, but device complexity and operator skill requirements increase
Solution Approach 1:
The patent extracts only the essential Doppler flow characteristics (velocity, direction, waveform patterns) from the complex ultrasound imaging process, converting them into simplified spectral displays that show flow velocity over time. This extraction allows automatic vessel identification based on flow patterns alone, removing the need for complex B-mode imaging and skilled interpretation while maintaining identification accuracy
Solution Approach 2:
The patent replaces the mechanical/visual inspection process (where operators visually examine ultrasound images to identify vessels) with an automated electronic system that analyzes Doppler spectral data using algorithms. This substitution eliminates the need for operator skill in image interpretation while maintaining or improving identification accuracy
2Measurement precision
If manual vessel identification by skilled sonographers is used, then measurement precision is improved, but productivity and ease of operation deteriorate
Solution Approach 1:
The system performs self-service by automatically analyzing Doppler spectral data and identifying vessels based on flow characteristics without requiring skilled operator intervention. The automated algorithms examine velocity patterns, direction, and waveform morphology to distinguish arteries from veins, enabling continuous monitoring by non-specialist personnel while maintaining identification accuracy
Solution Approach 2:
The system provides immediate automated feedback by continuously analyzing Doppler signals and providing real-time vessel identification and classification. This continuous automated feedback loop allows for persistent monitoring without the need for periodic skilled operator assessment, significantly improving productivity while maintaining precision
3Ease of operation
If Doppler spectral analysis is used for vessel identification, then ease of operation is improved, but measurement precision may deteriorate without skilled interpretation
Solution Approach 1:
The patent transforms the interpretation task from qualitative visual assessment to quantitative analysis of specific Doppler parameters including peak velocity, mean velocity, velocity variability, and waveform morphology. By changing the analysis from subjective visual interpretation to objective measurement of multiple flow parameters, the system maintains high precision while dramatically improving ease of operation
Solution Approach 2:
The patent adds temporal dimension to the analysis by examining velocity changes over the cardiac cycle through spectral Doppler displays. This time-based analysis of velocity waveforms provides additional discriminatory information that enables automated systems to accurately distinguish vessel types without requiring skilled visual interpretation, thereby improving both ease of operation and maintaining precision
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
Enables accurate and automatic vessel identification without skilled user input, improving probe placement accuracy and reducing errors in blood flow measurements.
Implementation Method 1
receiving ultrasound data acquired from a subject by way of an ultrasound probe
Implementation Method 2
generating color Doppler ultrasound data from the received ultrasound data
Implementation Method 3
obtaining pulse wave Doppler ultrasound data from the segmented vessel
Data Source
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AI summary
The invention provides a computer-implemented method for identifying the type of a vessel of a subject based on Doppler ultrasound data acquired from a subject. The computer-implemented method includes receiving ultrasound data acquired from the subject by way of an ultrasound probe and generating color Doppler ultrasound data from the received ultrasound data. A representation of a vessel of the subject is segmented from the color Doppler ultrasound data and pulse wave Doppler ultrasound data is obtained from the segmented vessel representation. A feature extraction algorithm is then applied to the pulse wave Doppler ultrasound data, thereby extracting a feature of the flow within the segmented vessel and the type of the vessel is identified as an artery or a vein based on the extracted feature of the flow.