3D Blood Vessel CPR Analysis for Automated Diameter Measurement
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Solution Overview
Problem
Current methods for analyzing vessel disease in 3D medical images, such as vessel stenosis and aneurysms, are inefficient and burdensome for users due to the manual effort required in identifying regions of interest and performing curved planar reconstruction (CPR) techniques.
Innovation Solution
A system and method that utilizes computing devices to automatically identify a region of interest in a blood vessel, determine center points, generate a CPR image, and measure the vessel diameter, with user-adjustable options for point selection and image generation, supported by AI training on marked 3D images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual identification of region of interest and manual CPR technique application is used, then user control and flexibility are maintained, but user burden and time consumption increase significantly
Solution Approach 1:
The system performs self-service by automatically identifying regions of interest, segmenting blood vessels, and generating CPR images without requiring manual user input for these tasks. The AI model processes medical images autonomously to complete analysis workflows that previously required extensive manual intervention.
Solution Approach 2:
The system performs preliminary actions by pre-identifying regions of interest and pre-segmenting blood vessels before the user needs to perform detailed analysis. This preparation eliminates the need for users to manually locate and define areas of interest, reducing their workload while maintaining system automation.
2Productivity
If automated identification and analysis is implemented, then efficiency and productivity are improved, but measurement precision and diagnostic accuracy may be compromised
Solution Approach 1:
The patent replaces manual mechanical measurement processes with automated computational algorithms. The system uses AI-based image processing and digital measurement techniques to automatically determine vessel diameters and other critical parameters, eliminating manual measurement while maintaining precision through computational accuracy.
Solution Approach 2:
The system incorporates feedback mechanisms where the AI model continuously refines its analysis based on the medical image data. The automated diameter measurement process includes validation steps that ensure measurement precision by comparing results against anatomical references and allowing for iterative improvement of the analysis accuracy.
3Loss of time
If automated CPR image generation is used, then time consumption is reduced, but device complexity and computational requirements increase
Solution Approach 1:
The system achieves multi-functionality by integrating multiple capabilities into a single platform: automated region of interest identification, blood vessel segmentation, CPR image generation, and diameter measurement. This universal system handles various vascular analysis tasks through unified AI models, reducing the need for separate specialized tools and lowering overall system complexity.
Solution Approach 2:
The patent introduces an intermediary AI processing layer that mediates between the input medical images and the required analysis outputs. This intermediate computational layer handles the complex transformations required to convert raw imaging data into diagnostic information, managing system complexity through a dedicated processing architecture.
Data Source
AI summary
Methods and systems for 3D image analysis including identifying a region of interest of a blood vessel in a medical image. The methods and systems include identifying a first point disposed on the blood vessel, the first point being a first center point of the blood vessel on a first side of the region of interest and identifying a second point disposed on the blood vessel, the second point being a second center point of the blood vessel on a second side of the region of interest. The methods and systems include generating a curved planar reconstruction (CPR) image of a portion of the blood vessel, the portion extending from the first point to the second point and including the region of interest and determining the diameter of the blood vessel at the region of interest.