Medical Image Retrieval With Variable Metadata Relevance Criteria
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods struggle to efficiently retrieve and display medical images with similar conditions to a target image due to the lack of standardized metadata definitions, making it difficult to automate the selection of relevant images for diagnosis.
Innovation Solution
A method is provided for displaying retrieved medical images by extracting metadata, assigning categories, and displaying associated images based on a variable relevance criterion level, which can be numerical or hierarchical, allowing for precise selection and placement of images based on metadata characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If automatic image retrieval is implemented without standardized metadata, then automation is achieved, but retrieval accuracy deteriorates due to lack of standardized definitions
Solution Approach 1:
The patent applies parameter changes by transforming unstructured image data into structured metadata with standardized parameters. The system extracts key features from medical images and represents them as standardized metadata parameters, enabling accurate automated retrieval while maintaining high retrieval accuracy through precise parameter standardization.
2Measurement precision
If manual reading of individual medical images is performed to select similar images, then retrieval accuracy is maintained, but time consumption increases
Solution Approach 1:
The patent implements self-service by enabling the system to automatically retrieve and rank similar medical images without requiring manual intervention. The automated retrieval system uses standardized metadata to independently perform image selection and ranking, significantly reducing time consumption while maintaining high retrieval accuracy through algorithmic processing.
Solution Approach 2:
The patent applies preliminary action by pre-extracting and pre-processing metadata from medical images before the actual retrieval operation. This preliminary processing creates a structured database of image features that can be quickly queried during retrieval operations, reducing the time needed for manual image reading and selection while maintaining accuracy.
3Measurement precision
If standardized metadata definitions are established, then retrieval accuracy is improved, but system complexity increases due to metadata standardization process
Solution Approach 1:
The patent applies segmentation by dividing the complex metadata standardization process into manageable segments. The system segments image data into distinct metadata categories (e.g., patient information, image characteristics, diagnostic features) and standardizes each segment independently, reducing overall system complexity while maintaining high retrieval accuracy through structured organization.
Data Source
AI summary
A method of displaying a retrieved medical image according to an embodiment of the present disclosure may include extracting metadata of a target medical image, obtaining at least one category for the extracted metadata and a category value corresponding to each category, and displaying medical images associated with a category value determined according to a variable relevance criterion level.