Vessel Flow Velocity Measurement Along 3D Curved Centerlines
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Solution Overview
Problem
Existing methods for determining fluid flow velocity in vessels, particularly in coronary vessels, lack accuracy and standardization, especially when dealing with curved or bent paths.
Innovation Solution
A method involving obtaining a natural length model of the vessel, dividing it into sections, and using intensity criteria to identify vessel sections in sequential images to determine flow velocity based on propagation length and time differences, with optional 3D modeling for enhanced accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional 2D image-based methods are used to determine flow velocity, then the measurement process is simple, but the accuracy is insufficient especially for curved vessels
Solution Approach 1:
The patent transforms 2D angiographic image data into a 3D centerline model of the vessel, enabling accurate measurement of propagation distance along the actual curved path of the vessel rather than straight-line distances in 2D images. This dimensional transformation resolves the accuracy problem for curved vessels while maintaining computational feasibility through automated centerline extraction algorithms.
Solution Approach 2:
The patent introduces a centerline model as an intermediary representation between the raw 2D images and the flow velocity calculation. This centerline serves as a 1D approximation of the vessel path that captures the curved geometry, allowing accurate distance measurement without requiring full 3D volumetric reconstruction, thus balancing accuracy and complexity.
2Reliability
If manual methods are used to measure propagation distance in images, then the process is simple to implement, but the results lack objectivity and standardization
Solution Approach 1:
The patent implements automated algorithms that extract vessel centerlines and track contrast propagation independently without requiring manual measurement intervention. The system automatically identifies the leading edge of contrast material, calculates propagation distance along the centerline, and determines flow velocity, eliminating observer bias and achieving standardized, repeatable measurements.
Solution Approach 2:
The patent replaces manual visual measurement methods with automated image processing algorithms. Instead of operators manually measuring distances on images, the system uses computational algorithms to extract centerlines, track contrast boundaries, and calculate velocities, thereby improving objectivity and reliability while increasing processing complexity.
3Measurement precision
If straight-line distance measurements are used in 2D images, then the calculation is straightforward, but the results are inaccurate for curved or bent vessel paths
Solution Approach 1:
The patent moves from 2D straight-line distance measurements to 3D centerline-based distance measurements. By reconstructing the vessel centerline in three dimensions and measuring propagation distance along this curved path, the system accurately captures the true distance contrast material travels through bent vessels, resolving the inaccuracy problem while using automated algorithms to manage the increased complexity.
Data Source
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AI summary
Image data of contrast dye in a vessel in a body is acquired for determining flow rate. Based on images acquired under and angle relative to one another, a three-dimensional model of the vessel is constructed and length of a vessel section is determined. A series of at least two images, apart in time, under a first angle is assessed for determining progress of a front of the dye bolus in the vessel in time. In the images, the vessel may be segmented and brightness or a derivative thereof over at least one of time and distance may be assessed to determine the front. Progress distance is mapped to the three-dimensional model, for example by mapping segments from the image to the model, to obtain a more accurate and natural distance of progress over time. Flow rate is determined by natural progress distance over progress time.