Automated Intracranial Aneurysm Morphological Parameter Measurement
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for measuring intracranial aneurysm images are manual, slow, inconsistent, and unable to accurately measure complex morphological parameters, lacking the capability for fully automated and consistent measurements.
Innovation Solution
An automated method and system that segments intracranial parent artery and aneurysm images from three-dimensional DICOM data using region growing and surface reconstruction techniques to compute morphological parameters such as volume, diameter, and inflow angle, ensuring quick and consistent measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual measurement by experienced physicians is used, then measurement capability is available, but measurement speed is slow and consistency is poor
Solution Approach 1:
The system enables automated self-measurement of aneurysm parameters through computer-aided algorithms. The measurement system automatically segments the aneurysm from DSA images, calculates morphological parameters, and generates reports without requiring manual physician intervention for each measurement task, thereby improving both speed and consistency.
Solution Approach 2:
The patent replaces the manual mechanical measurement process with an automated computer-based system. The computer automatically performs image segmentation, parameter calculation, and measurement tasks that were previously done manually by physicians, eliminating human variability and significantly improving measurement efficiency and consistency.
2Measurement precision
If conventional manual measurement methods are used, then simple parameters can be measured, but complex parameters cannot be measured accurately
Solution Approach 1:
The computer-aided measurement system is designed to measure multiple types of parameters simultaneously - both simple parameters (such as segment distance) and complex parameters (such as volume, surface area, and three-dimensional morphology). This multi-functional capability allows the system to handle diverse measurement requirements within a single automated framework.
Solution Approach 2:
The system transforms complex morphological parameters into measurable quantities through automated image processing. By using computer algorithms to segment the aneurysm and calculate various parameters (volume, surface area, diameter, etc.), the system converts complex geometric measurements into precise numerical values that can be automatically computed and analyzed.
3Extent of automation
If traditional model simulation or manual measurement methods are used, then some measurements can be performed, but fully automated measurement cannot be achieved
Solution Approach 1:
The system performs preliminary automated segmentation of the aneurysm from DSA images before measurement. By pre-processing the images to isolate the aneurysm structure and define its boundaries automatically, the system prepares the data in advance for precise parameter calculation, ensuring both full automation and measurement consistency.
Solution Approach 2:
The patent completely replaces manual measurement operations with automated computer-based processing. The computer system automatically segments images, identifies aneurysm boundaries, calculates morphological parameters, and generates measurements without human intervention, achieving full automation while maintaining high precision through consistent algorithmic processing.
Data Source
AI summary
A method and a system for measuring morphological parameters of an intracranial aneurysm image, the method comprises: segmenting an intracranial parent artery image from three-dimensional DICOM data of DSA (S101); segmenting the intracranial aneurysm image on the intracranial aneurysm image (S102); and measuring morphological parameters of the intracranial aneurysm image (S103). The method and the system for measuring the morphological parameters of the intracranial aneurysm image as disclosed may implement automated measurement of the intracranial aneurysm image, quickly measure morphological parameters of the intracranial aneurysm image, and guarantee consistency between measurements of morphological parameters of the aneurysm image.