Eye Rotation Angle Detection Using Direct Image Comparison
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Solution Overview
Problem
Existing methods for determining the rotation angle of an eye, particularly cyclotorsion, during ophthalmological treatments require specific lighting conditions, manual intervention, or iterative computations, making them cumbersome and less effective.
Innovation Solution
An ophthalmological treatment device using a processor and camera to determine the rotation angle by comparing a reference image taken in an upright position with a current image in a reclined position, employing a direct solver and neural networks to identify non-local features and calculate the rotation angle efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual marking methods are used to determine eye rotation angle, then the measurement can be performed, but the process becomes time-consuming and requires manual intervention
Solution Approach 1:
The patent replaces manual mechanical marking methods with an automated image processing system. The processor automatically captures images of the eye, detects features (blood vessels, iris patterns), and calculates the rotation angle through computational algorithms, eliminating the need for manual marking and significantly reducing treatment time while maintaining measurement precision.
Solution Approach 2:
The system enables self-service measurement by automatically performing all steps of rotation angle determination without operator intervention. The image capture, feature detection, and angle calculation are all executed autonomously by the device's processor, allowing the measurement process to serve itself and eliminating time-consuming manual operations.
2Measurement precision
If iterative optimization computations are used to determine cyclotorsion angle, then accurate measurement can be achieved, but the computation time increases
Solution Approach 1:
The patent extracts and utilizes naturally occurring anatomical features (blood vessels in the sclera, iris patterns) as reference markers for measurement. By leveraging these pre-existing structural features rather than requiring iterative optimization against artificial markers, the system achieves accurate cyclotorsion angle measurement through direct geometric calculation, significantly improving computation speed while maintaining precision.
Solution Approach 2:
The system performs preliminary capture of eye images before treatment begins, allowing the rotation angle to be determined in advance. The processor analyzes the captured images to establish the treatment model with proper orientation, so that during actual treatment, the pre-determined angle can be applied directly without requiring real-time iterative computation, thus enhancing both accuracy and productivity.
3Adaptability or versatility
If diagnostic images and treatment images are taken under different conditions, then comprehensive data can be collected, but alignment and comparison become difficult
Solution Approach 1:
The patent employs universal anatomical features (blood vessels, iris patterns) that remain consistent across different imaging conditions and positions. These features serve as reliable reference points whether the eye is imaged in upright or supine position, allowing accurate alignment and comparison of diagnostic and treatment images despite varying capture conditions, thus maintaining measurement precision while preserving data collection flexibility.
Solution Approach 2:
The system accounts for parameter changes between diagnostic and treatment phases by detecting and measuring the rotation angle that occurs when the patient changes position. The processor calculates the transformation parameters (rotation angle, translation) needed to align images taken under different conditions, enabling accurate comparison and superposition of diagnostic and treatment images while maintaining measurement precision.
4Measurement precision
If multiple diagnostic images and artificial markers are used to determine eye rotation, then measurement accuracy can be improved, but the device complexity and manual intervention increase
Solution Approach 1:
The system utilizes the eye's own anatomical structures (blood vessels, iris patterns) as natural reference markers, eliminating the need for artificial markers. The processor automatically detects and tracks these self-service features across images, achieving accurate rotation angle measurement without adding device complexity or requiring manual marker application, thus simplifying the overall measurement system.
Data Source
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AI summary
An ophthalmological treatment device (1) comprising a processor (11) and a camera (12) for determining a rotation of an eye (21) of a person, the processor (11) configured to: receive a reference image of the eye (21), the reference image having been recorded with the person in an upright position by a separate diagnostic device; record, using the camera, a current image of the eye (21), the current image being recorded with the person in a reclined position; and determine a rotation angle of the eye (21) by comparing the reference image to the current image using a direct solver.