Medical Diagnostic Image Processing Apparatus for Collateral Circulation Detection
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Solution Overview
Problem
Current medical diagnostic image processing techniques for head perfusion imaging in X-ray computed tomography struggle to effectively identify collateral circulation due to the reliance on user observation of time-series blood vessel images, making it difficult to detect collateral circulation candidates.
Innovation Solution
A medical diagnostic image processing apparatus that includes a lesion candidate region extraction unit and a display unit, which compares pixel values of perfusion images with thresholds to extract and display lesion candidate regions, such as collateral circulation or bypass blood vessels, enhancing image diagnosis by superimposing these regions onto blood vessel images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If time-series blood vessel images are used for observation, then the user can observe blood vessel changes, but it becomes difficult to find collateral circulation due to reliance on manual image observation
Solution Approach 1:
The system automatically extracts and highlights collateral circulation regions without requiring manual analysis. The processing unit autonomously identifies blood vessel changes and generates diagnostic information, allowing the system to serve itself in the detection process rather than relying solely on user observation.
Solution Approach 2:
The patent replaces manual mechanical image observation with automated computer processing. The processing unit uses algorithmic analysis to detect and measure collateral circulation, substituting the mechanical act of manually reviewing images with automated digital processing and highlighting mechanisms.
2Productivity
If automated processing is introduced to extract lesion candidate regions, then the efficiency of diagnosis is improved, but the device complexity increases
Solution Approach 1:
The processing unit divides the complex task of collateral circulation detection into segmented steps: extracting blood vessel images, identifying changes, determining lesion candidate regions, and generating diagnostic information. This segmentation allows complex processing to be broken down into manageable functional modules.
Solution Approach 2:
The patent introduces an intermediary processing layer between raw blood vessel images and final diagnostic conclusions. The processing unit acts as an intermediary that automatically analyzes images, extracts features, and generates diagnostic information, mediating between the raw data and the user's diagnostic needs.
Data Source
AI summary
The invention improves the quality of image diagnosis by a user. An image processing unit compares each pixel value of a perfusion image with a threshold, and extracts a lesion candidate region as a collateral circulation candidate or bypass blood vessel candidate from the perfusion image based on a comparison result. The image processing unit displays the lesion candidate region together with a blood vessel image representing the spatial distribution of blood vessels in a head.