Diagnostic Reference Image Extraction for Faster Registration
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional systems require significant user effort and time to select reference images from a large number of images for each imaging method, making the process inconvenient.
Innovation Solution
A reference image providing apparatus and method that automatically extracts and provides reference images or candidate images from diagnostic images using an extractor and provider, reducing the need for manual selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If reference images are manually selected from a large number of images for each imaging method, then the quality and suitability of reference images can be ensured, but the time and labor required for registration increases significantly
Solution Approach 1:
The system automatically extracts candidate reference images from diagnostic images using image analysis algorithms, enabling the system to perform the reference image selection task itself without requiring manual intervention. The extractor automatically identifies and extracts images that meet the criteria for reference images based on their diagnostic quality and relevance.
Solution Approach 2:
The manual mechanical process of selecting reference images by human operators is replaced with an automated image processing system that uses computational algorithms to analyze diagnostic images and extract suitable reference images. This substitution of manual mechanical selection with automated computational analysis resolves the contradiction between ensuring quality and reducing time investment.
2Ease of operation
If reference images are manually selected and registered in advance, then accurate imaging references are available for diagnosis, but the operation complexity and user effort increase
Solution Approach 1:
The system performs automatic extraction of reference images without requiring user intervention in the selection process. The extractor autonomously analyzes diagnostic images and identifies suitable reference images, making the system self-sufficient in maintaining the reference image database without complex manual registration operations.
3Adaptability or versatility
If a large number of images are available for selection, then the likelihood of finding suitable reference images increases, but the time and effort required to select from them increases
Solution Approach 1:
The extractor automatically extracts candidate reference images from the pool of diagnostic images based on predefined criteria and image analysis. This extraction process identifies and isolates the most suitable images without requiring manual review of the entire collection, thus maintaining high adaptability while improving registration efficiency.
Solution Approach 2:
The manual process of searching and selecting reference images from a large collection is replaced with automated image analysis and extraction algorithms. This substitution enables the system to efficiently process large numbers of images and identify suitable reference images without the time and effort constraints of manual selection.
Data Source
AI summary
A reference image providing apparatus capable of reducing user's labor required for registration of a reference image, wherein the reference image providing apparatus includes an extractor configured to extract a reference image or a candidate image of the reference image from diagnostic images used for diagnosis, the reference image serving as an imaging reference for determining whether or not an image can be used for diagnosis; and a provider configured to provide an extraction result. For example, when the reference image is not set, the extractor extracts the reference image or the candidate image.


