Retinal Thickness Circular Profile Analysis for Local Variation Detection
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Solution Overview
Problem
Conventional methods for diagnosing eye disorders using retinal thickness measurements lack sensitivity in detecting abrupt changes, local variations, and association with anatomical features, and do not effectively track the progression of retinal defects over time.
Innovation Solution
Characterizing retinal parameters as a function of polar angle, calculating integrals of reference and measured parameter functions over specific intervals, and using a more nuanced color coding scheme to provide detailed thickness profiles and track abnormalities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional color codes with coarse granularity are used to display retinal thickness data, then the display is simple and easy to interpret, but the detection sensitivity for abrupt changes and local variations is insufficient
Solution Approach 1:
The retinal circumference is divided into multiple arcs, and each arc is further segmented into segments for detailed analysis. This segmentation allows local variations to be detected while maintaining overall simplicity through systematic organization of the divided regions.
Solution Approach 2:
Different color codes are assigned to different arcs and segments based on their specific thickness characteristics. This local differentiation enables precise detection of local variations while maintaining a simple color-coded display system that is easy to interpret.
2Device complexity
If the retinal circumference is divided into a fixed number of arcs, then the display format is standardized, but the detection of local variations becomes highly variable depending on arc length and orientation
Solution Approach 1:
Each arc is subdivided into multiple segments, allowing the system to maintain standardized arc divisions while achieving consistent local variation detection through further segmentation that reduces the impact of arc length and orientation variations.
Solution Approach 2:
The analysis transitions from a single arc-level dimension to a two-dimensional arc-segment structure. This additional segmentation dimension provides more granular control over detection sensitivity while maintaining the standardized arc framework.
3Device complexity
If conventional circle scan methods are used to measure retinal thickness, then the measurement process is simple, but the ability to track progression of retinal defects over time is limited
Solution Approach 1:
The retinal circumference is divided into arcs and segments that can be individually tracked over time. This segmentation enables precise monitoring of defect progression in specific regions while maintaining the simplicity of the overall circle scan measurement approach.
Solution Approach 2:
The system provides feedback by comparing thickness measurements across multiple time points for each arc and segment. This enables reliable tracking of defect progression while building upon the simple circle scan measurement foundation.
4Productivity
If simple arc-based display is used for retinal thickness data, then rapid assessment is enabled, but detailed tracking of defect growth and association with anatomical features is not possible
Solution Approach 1:
The retinal circumference is divided into arcs and further segmented into segments, enabling both rapid overall assessment and detailed defect tracking. The hierarchical structure allows clinicians to quickly evaluate the entire retina and then focus on specific segments requiring detailed examination.
Solution Approach 2:
Different levels of detail are provided for different regions based on their clinical significance. The arc-segment structure enables detailed characterization of specific defect locations while maintaining rapid assessment capability for the overall retinal status.
Data Source
AI summary
Certain diseases of the retina are diagnosed by circular profile analysis of retinal parameters, such as thickness. Retinal thickness around a user-defined circle on the retina is measured by three-dimensional optical coherence tomography or other ophthalmological techniques. Abnormally thin regions are identified by comparing a measured function of thickness vs. polar angle to a reference function of thickness vs. polar angle. A degree of abnormality is characterized by the ratio of the integral of the measured thickness function to the integral of the reference thickness function over the abnormally thin region, as specified by a range of polar angles.


