Iris Registration Correlation for Cyclotorsion-Accurate Laser Surgery
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Solution Overview
Problem
Existing iris registration methods for ophthalmic surgical procedures, particularly in cataract surgery, fail to accurately account for cyclotorsion when drug-induced pupil dilation is used, leading to alignment errors due to the rotation of the eye and variations in patient-system alignment parameters.
Innovation Solution
A method and system that utilize a global correlation algorithm to register the iris by generating pre-treatment and treatment images of the eye, correcting the orientation of a therapeutic laser beam based on a correlation function defined for these images, and employing a laser control system to adjust the laser beam's orientation accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If drug-induced pupil dilation is used for cataract surgery, then the surgical procedure can be performed, but accurate iris registration becomes impossible with existing landmark-based algorithms due to pupil rotation and distortion
Solution Approach 1:
The patent changes the fundamental parameters used for registration from landmark-based coordinates to frequency-domain correlation functions. By transforming the iris images into the frequency domain and comparing spectral characteristics, the system achieves rotation-invariant registration that works regardless of pupil dilation state, thereby resolving the contradiction between surgical versatility and measurement precision
Solution Approach 2:
The patent replaces the mechanical/geometric landmark-matching approach with a signal processing-based correlation method. Instead of manually or algorithmically matching specific points in the iris, the system uses Fourier transform-based correlation functions that compare the overall spectral patterns, making the registration robust to pupil dilation and rotation effects
2Reliability
If the patient's head position or eye rotation changes between diagnostic imaging and surgical procedure, then cyclotorsion occurs, but existing registration methods fail to compensate for this rotation
Solution Approach 1:
The patent implements a feedback mechanism where the correlation function continuously measures the alignment between diagnostic and surgical device coordinate systems. The system calculates the correlation at different rotational offsets and uses the maximum correlation value to determine the correct cyclotorsion compensation angle, automatically adjusting for head tilt and eye rotation changes
Solution Approach 2:
The patent performs preliminary correlation analysis between the diagnostic device image and the surgical device image to determine the cyclotorsion angle before the actual surgical procedure begins. This preliminary registration allows the surgical device to pre-compensate for anticipated head position changes, ensuring accurate alignment from the start of the procedure
3Adaptability or versatility
If landmark-based iris registration algorithms are used, then registration can be performed in non-dilated eyes, but these algorithms cannot be applied when the pupil is dilated during cataract surgery
Solution Approach 1:
The patent replaces the complex landmark-detection and matching algorithm with a simpler frequency-domain correlation approach. By transforming images to the frequency domain and comparing spectral patterns, the system achieves rotation-invariant registration that works with dilated pupils without requiring complex landmark identification, thus improving adaptability while managing algorithmic complexity
Solution Approach 2:
The patent changes the operational parameters of the registration algorithm from spatial-domain landmark coordinates to frequency-domain spectral characteristics. This parameter transformation allows the algorithm to work with dilated pupils where traditional landmarks are not visible, achieving versatility across different pupil states
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate iris registration during cataract surgery, accounting for cyclotorsion and ensuring precise alignment of surgical procedures even with drug-induced pupil dilation, thereby improving the accuracy of astigmatism correction and toric intra-ocular lens positioning.
Implementation Method 1
an analyzer that has a light source that illuminates the eye and one or more detectors that receive reflected light off from the eye and generate images of the eye
Implementation Method 2
a laser source that emits a therapeutic laser beam toward an eye
Data Source
AI summary
A method that includes illuminating an eye with light at a first time and a second time and generating a first image of the eye based on the light that illuminates the eye at the first time. The method includes generating a second image of the eye based on the light that illuminates the eye at the second time. The method further includes positioning a laser source relative to the eye, wherein the laser source generates a therapeutic laser beam to be directed to the eye, wherein the first time is just prior to the therapeutic laser beam being directed to the eye and the second time is prior to the first time. The method further includes correcting orientation of the laser source relative to the eye based on a correlation function that is defined for the first and second images of the eye.