Automated Aortic Pathology Detection in Tomograph Scans
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Solution Overview
Problem
Current methods for detecting and characterizing aortic pathologies such as aortic aneurysms and dissections are often time-consuming and require user intervention, which can delay optimal treatment in life-threatening medical emergencies.
Innovation Solution
A computer-based system and method that analyzes tomograph scan images to identify image features associated with aortic pathologies, determining the presence, type, and extent of conditions like aortic dissection or aneurysm, and suggests appropriate treatment options without user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If current manual methods are used for detecting and characterizing aortic pathologies, then diagnostic accuracy can be maintained through user intervention, but diagnostic time is excessively long which delays optimal treatment
Solution Approach 1:
The system enables self-service automation by having the computer automatically perform image analysis, pathology detection, and treatment recommendation without requiring user intervention. The computer system independently processes tomograph scan images, identifies aortic pathologies, and generates diagnostic conclusions, allowing the diagnostic process to serve itself rather than relying on manual user operations.
Solution Approach 2:
The patent replaces the mechanical manual analysis process with an automated computer-based image analysis system. Instead of users manually examining tomograph scan images, the system uses computer algorithms to automatically detect image features, characterize aortic pathologies, and suggest treatments, substituting human mechanical inspection with automated computational analysis.
2Productivity
If automated computer-based analysis is implemented, then diagnostic speed is significantly improved, but system complexity increases requiring advanced image processing capabilities
Solution Approach 1:
The image analysis process is segmented into distinct functional modules: receiving tomograph scan images, analyzing for image features, identifying aortic pathologies, and suggesting treatments. This segmentation allows each module to be independently optimized and managed, reducing overall system complexity while maintaining high diagnostic throughput through parallel processing capabilities.
3Measurement precision
If comprehensive image feature analysis is performed to accurately characterize aortic pathologies, then measurement precision is improved, but computational requirements and processing time increase
Solution Approach 1:
The system performs partial analysis by focusing on detecting and characterizing only the specific image features relevant to aortic pathologies rather than analyzing all possible image characteristics. This selective approach maintains high measurement precision for pathology characterization while reducing unnecessary computational energy consumption by avoiding excessive analysis of irrelevant features.
Data Source
AI summary
According to one or more embodiments, a method, a computer program product, and a computer system for detecting and characterizing aortic pathologies are provided. The method may include receiving, by a computer, one or more tomograph scan images corresponding to a patient's aorta. The one or more received tomograph scan images may be analyzed by the computer for one or more image features associated with one or more aortic pathologies, such as aortic dissection or an aortic aneurysm. One or more image features associated with the one or more aortic pathologies may be identified in the one or more analyzed tomograph scan images, which may allow the determination of an aortic pathology associated with the patient's aorta based on the identification of the image features. A portion of the aorta and one or more branch arteries corresponding to the determined aortic pathology may then be identified.