Ophthalmic Diagnostic Interface for OCT Data Segmentation and Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current ophthalmic diagnostic systems lack efficient tools for displaying, analyzing, and interpreting large volumes of data from multiple diagnostic modalities, such as OCT and visual field tests, which limits their diagnostic accuracy and clinical application in monitoring diseases like glaucoma.
Innovation Solution
A customizable graphical user interface that allows users to create tailored views, order scans based on specific pathologies, bookmark scans, access a reference library, and perform real-time z-tracking, enabling optimized data acquisition, display, and analysis, including the ability to use user-generated normative databases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple diagnostic modalities are integrated to improve diagnostic accuracy, then the quantity and complexity of data to be analyzed increases, making the system more complex
Solution Approach 1:
The system segments the complex data from multiple diagnostic modalities into separate, organized categories (OCT data, visual field data, fundus images) with dedicated display panels and analysis tools for each modality, making the overall complex system manageable through structured organization
Solution Approach 2:
The software platform provides universal functionality to handle multiple diagnostic modalities through a single integrated system, allowing clinicians to access, display, and analyze data from different sources using consistent interfaces and standardized protocols
2Ease of operation
If standard manufacturer protocols are used for data display, then ease of operation is maintained, but adaptability to specific clinical needs and pathologies is reduced
Solution Approach 1:
The system dynamically adjusts display parameters, scan protocols, and analysis settings based on the specific pathology being evaluated and the clinical scenario, allowing the interface to adapt from static standard protocols to dynamic customized configurations
Solution Approach 2:
The system applies different display and analysis characteristics to different data types and clinical scenarios, providing localized optimization for each modality and pathology while maintaining overall system coherence
3Measurement precision
If larger volumes of data are collected from OCT scans, then measurement precision and diagnostic information increase, but the time required for analysis and interpretation increases
Solution Approach 1:
The system performs preliminary automated analysis, segmentation, and organization of large OCT datasets during data acquisition, pre-processing the information to reduce the time required for subsequent clinical interpretation while maintaining measurement precision
Solution Approach 2:
The system provides real-time feedback and automated alerts when significant findings are detected in the large datasets, allowing clinicians to focus their analysis time on critical areas rather than reviewing all data sequentially
Data Source
AI summary
Improvements to user interfaces for ophthalmic imaging systems, in particular Optical Coherence Tomography (OCT) systems are described to improve how diagnostic data are displayed, analyzed and presented to the user. The improvements include user customization of display and reports, protocol driven work flow, bookmarking of particular B-scans, accessing information from a reference library, customized normative databases, and ordering of follow-up scans directly from a review screen. A further aspect is the ability to optimize the contrast and quality of displayed B-scans using a single control parameter. Virtual real time z-tracking is described that maintains displayed data in the same depth location regardless of motion.