Visual Field Map Reconstruction Using SORS
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Solution Overview
Problem
Standard Automated Perimetry methods are inefficient in obtaining accurate visual field maps due to high test time and noise in responses, with existing strategies failing to achieve a balance between speed and accuracy.
Innovation Solution
The Sequentially Optimized Reconstruction Strategy (SORS) method, which determines the optimal order and locations for testing based on correlations between visual field locations, uses a meta-strategy combining traditional staircase methods or Bayesian strategies to estimate perceived sensitivity thresholds efficiently, reducing the number of required measurements and improving accuracy-speed trade-off.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple brightness levels at all locations are tested multiple times to reduce response noise, then measurement accuracy is improved, but test time increases significantly (more than 15 minutes per eye)
Solution Approach 1:
The patent applies preliminary action by pre-defining a prioritized sequence of test locations based on their information value for visual field reconstruction. High-value locations (those that provide most information about visual field defects) are tested first, allowing the system to build an accurate visual field map early in the examination. This preliminary ordering enables the system to stop testing when sufficient accuracy is achieved, avoiding the need to test all locations multiple times.
Solution Approach 2:
The patent implements partial action by testing only a subset of locations with the highest information value rather than all locations. The system identifies and tests approximately 10-15 key locations out of the full 54-location Humphrey visual field test, which provides sufficient information for accurate visual field reconstruction while reducing test time by more than half.
2Productivity
If testing is performed at only a handful of locations to reduce test time, then test speed is improved, but visual field map accuracy deteriorates
Solution Approach 1:
The patent applies local quality by assigning different priorities to different test locations based on their information value. Rather than treating all locations equally, the system identifies specific locations (such as those in the central visual field or areas prone to glaucomatous defects) that provide disproportionate information about visual field status. These high-value locations are tested with greater emphasis, while lower-value locations are tested less or not at all.
Solution Approach 2:
The system performs preliminary analysis to determine the optimal set of test locations before the actual visual field test begins. This pre-calculation of location priorities allows the system to select the most informative subset of locations in advance, ensuring that even with reduced testing, the resulting visual field map maintains high accuracy.
3Measurement precision
If traditional staircase methods or Bayesian strategies are used to determine stimulus intensity, then perceived sensitivity threshold measurement is achieved, but the number of required measurements is large and test time is extended
Solution Approach 1:
The patent introduces an intermediary computational model that predicts perceived sensitivity thresholds at untested locations based on measurements from a small subset of high-value locations. This graphical model acts as a mediator, translating limited direct measurements into a complete visual field map by propagating information across the visual field space, thereby reducing the number of actual measurements needed while maintaining accuracy.
Solution Approach 2:
The system performs partial measurement by obtaining perceived sensitivity threshold data at only the most informative locations rather than at all locations. The graphical model then completes the visual field map by inferring values at untested locations, achieving full visual field coverage with fewer than half the measurements required by traditional methods.
Data Source
AI summary
The invention relates to a method for obtaining a visual field map of an observer, particularly a perimetry method, wherein a plurality of test locations in front of the observer is provided, at each test location of a subset of said plurality a respective perceived sensitivity threshold 5 is measured, wherein at least one light signal is provided at the respective test location, and wherein it is monitored whether said observer observes said at least one light signal, and wherein for each test location a respective estimate of the perceived sensitivity threshold is derived from the previously measured perceived sensitivity thresholds of said subset, and wherein said light signal is provided at a light intensity value derived from the estimate of the 10 perceived sensitivity threshold of said respective test location.