Aneurysm Classification via AI Vasculature Masking
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Solution Overview
Problem
Current methods for evaluating and treating intracranial aneurysms are inadequate due to variability in dilation measurements and lack of accurate methods for assessing the stage and progression of the disease, leading to suboptimal treatment decisions.
Innovation Solution
A method using a computer system to generate a report that classifies and quantitatively analyzes aneurysms by segmenting medical image data, generating a binary vasculature mask, and applying a trained machine learning algorithm to produce a probability map and quantitative parameters, thereby providing a more objective and accurate analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual dilation measurements are used by radiologists, then clinical assessment can be performed, but measurement variability and subjectivity increase
Solution Approach 1:
The patent replaces manual mechanical measurement methods with an automated image processing system that uses algorithms to detect and measure aneurysm dimensions. The system automatically identifies aneurysm boundaries and calculates dilation metrics, eliminating human variability and subjectivity from the measurement process while maintaining high precision through computational analysis.
2Measurement precision
If automated image processing is implemented, then measurement objectivity and precision improve, but system complexity increases
Solution Approach 1:
The patent divides the complex image processing task into distinct functional modules: pre-processing module for image enhancement, detection module for identifying aneurysm locations, measurement module for calculating dimensions, and analysis module for generating clinical reports. This segmentation allows each module to be optimized independently and simplifies system implementation while achieving high measurement precision through coordinated operation of specialized components.
Data Source
AI summary
Aneurysms are classified and quantitatively analyzed based on medical image data acquired from a subject. In general, one or more algorithms are implemented to automatically classify, or otherwise diagnose, and measure aneurysms and their change over time. These algorithms make use of artificial intelligence and deep learning to develop quantitative analytics that can be consolidated into diagnostic reports.