Medical Image Annotation System with Cross-Modality Data Relationships
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Solution Overview
Problem
Conventional medical imaging systems lack the ability to effectively integrate and maintain relationships between images and textual information from different modalities and specialties, leading to fragmented data access and inadequate decision-making support for multi-disciplinary teams.
Innovation Solution
A system that processes, aggregates, and annotates medical images across various modalities and specialties, using a processor and annotation service module to establish and maintain data relationships, allowing for the generation and storage of annotations as vector information linked to the images, enabling cross-media distribution and interactive viewing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If images and textual information from different modalities and specialties are maintained in separate systems, then data management for each specialty can be simplified and standardized, but data integration and relationship maintenance become complex and fragmented
Solution Approach 1:
The patent merges images and textual information from different modalities and specialties into a single integrated data set, allowing all data to be managed together while maintaining their individual relationships through common identifiers. This resolves the contradiction by combining previously separate systems into one unified system that handles both simplicity and integration needs.
Solution Approach 2:
The patent creates a universal data structure that can accommodate multiple types of data (images, text, metadata) from various sources and modalities. This multi-functional framework allows the system to handle diverse data types uniformly, simplifying management while enabling comprehensive integration across different specialties.
2Measurement precision
If annotations are generated for individual images from different modalities, then specific image details can be accurately annotated, but maintaining relationships across multiple images and modalities becomes difficult
Solution Approach 1:
The patent introduces common identifiers as intermediary elements that link annotations across multiple images from different modalities. These identifiers act as mediators that preserve relationship information while allowing precise annotations on individual images, resolving the contradiction between annotation accuracy and relationship maintenance.
Solution Approach 2:
The patent adds a new dimension to annotation storage by incorporating cross-image and cross-modality relationship information alongside traditional image-specific annotations. This dimensional expansion allows the system to maintain both precise image-level annotations and broader relationship context simultaneously.
3Adaptability or versatility
If a unified system integrates data from multiple sources and modalities, then comprehensive decision-making support can be provided, but system complexity and data aggregation challenges increase
Solution Approach 1:
The patent segments the unified data system into organized components including images, textual information, metadata, and annotations, each with defined structures and relationships. This segmentation allows the complex unified system to be managed through modular, organized units while maintaining comprehensive integration capabilities for decision-making support.
Data Source
AI summary
The present disclosure is related to visual annotations on medical images. A system may include a processor configured to process input data and identify a relationship amongst received input data in a data set. The system may also include an aggregator coupled to the processor and configured to receive processed data from the processor and aggregate data within the data set while maintaining one or more data relationships within the data set. Further, the system may include an annotation service module coupled to the aggregator and configured to generate at least one annotation that is maintained across at least a portion of the data within the data set.