Rules-Based Medical Image Transfer and Rendering
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Solution Overview
Problem
Current medical imaging systems face challenges in efficiently distributing, viewing, and prioritizing large volumes of digital medical images across various network and viewing conditions, often requiring improved methods for managing and rendering images based on specific criteria such as slice thickness and image series attributes.
Innovation Solution
The implementation of a rules-based approach that classifies medical images as 'thin slices' based on criteria like maximum thickness or quantity, allowing for selective transfer and display of these images, with options to not transfer, transfer with lower priority, or process differently, and includes user-defined rules for rendering medical images to match desired slice thickness or increment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all medical images are transferred to ensure complete data availability, then image completeness is improved, but network bandwidth consumption and storage requirements increase
Solution Approach 1:
The patent segments medical images into different categories based on their characteristics (e.g., thin slices vs. thick slices, different image planes). This segmentation allows the system to apply different transfer strategies to different image types, transferring only necessary images to remote devices while maintaining completeness for critical diagnostic images.
Solution Approach 2:
The patent applies local quality by making image transfer decisions based on specific local characteristics of each image or image series (such as slice thickness, image plane, and diagnostic importance). This allows selective transfer of images that meet specific criteria to particular devices, optimizing both bandwidth usage and image availability.
2Quantity of substance
If thin slice images are selectively transferred based on criteria, then bandwidth and storage efficiency are improved, but image availability for certain diagnostic needs may be reduced
Solution Approach 1:
The patent implements dynamic image transfer rules that can be configured based on user needs, device capabilities, and diagnostic requirements. The system can adaptively adjust which images are transferred based on real-time conditions, ensuring that critical diagnostic images are available when needed while optimizing bandwidth usage during normal operations.
Solution Approach 2:
The system incorporates feedback mechanisms where user preferences and diagnostic requirements can modify transfer decisions. This allows the system to learn from usage patterns and adjust image transfer strategies to balance bandwidth efficiency with ensuring image availability for specific diagnostic tasks.
3Adaptability or versatility
If image transfer rules are made flexible and configurable, then adaptability to different viewing conditions is improved, but system complexity increases
Solution Approach 1:
The patent creates a universal image transfer rule engine that can handle multiple image types, transfer scenarios, and device configurations through a single unified system. This multi-functional approach allows complex viewing conditions to be managed through standardized rule templates, reducing the actual complexity despite the flexibility.
Solution Approach 2:
The system manages adaptability by changing parameters within predefined rule frameworks rather than requiring complex custom configurations. Users can adjust parameters like slice thickness thresholds, image plane preferences, and priority levels within established rule structures, maintaining flexibility while avoiding system complexity.
Data Source
AI summary
Systems and methods that allow transfer and display rules to be defined based on one or more of several attributes, such as a particular user, site, device, and/or image/series characteristic, as well as whether individual images and/or image series are classified as thin slices and/or based on other characteristics, and applied to medical images in order to determine which images and/or image data are analyzed, downloaded, viewed, stored, rendered, processed, and/or any number of other actions that might be performed with respect to medical image data. The system and methods may include image analysis, image rendering, image transformation, image enhancement, and/or other aspects to enable efficient and customized review of medical images.