Eye Surgical Laser Tissue Geometry Calculation
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Solution Overview
Problem
Current methods for determining tissue geometry for eye surgical lasers require high computing power and long processing times, relying on iterative calculations and assumptions based on literature values, which can lead to errors and inefficiencies.
Innovation Solution
A method that uses a control device to ascertain corneal and ocular wavefronts from examination data, applying physical models based on reflection and refraction laws to calculate the tissue geometry to be removed, allowing for direct measurement and reduced computational requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If iterative ray tracing calculations are used to determine tissue geometry, then manufacturing precision is improved, but computing time and computing power requirements increase
Solution Approach 1:
The patent performs preliminary measurements of the actual eye parameters (corneal curvature, lens curvature, vitreous body curvature, refractive indices) before the surgical procedure. These measured values are stored and used directly in the wavefront calculation, eliminating the need for iterative calculations during treatment planning and reducing computing time while maintaining precision
Solution Approach 2:
The patent replaces the iterative mechanical ray tracing calculation system with an analytical wavefront calculation system based on measured physical parameters. By using direct wavefront difference calculations instead of iterative simulations, the system achieves the same precision with significantly reduced computational burden
2Manufacturing precision
If iterative ray tracing calculations are used to determine tissue geometry, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The patent replaces the complex iterative ray tracing calculation system with a simpler analytical wavefront calculation system. The new system uses direct mathematical formulas based on measured eye parameters, eliminating the need for complex iterative algorithms while maintaining the same level of precision in tissue geometry determination
3Device complexity
If literature values are used for eye model assumptions, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The system performs self-measurement of the patient's actual eye parameters (corneal curvature, lens curvature, vitreous body curvature, refractive indices) using integrated measurement devices. These self-measured values replace literature-based assumptions, providing personalized accurate data for each patient while maintaining a relatively simple device architecture
Solution Approach 2:
The patent changes the parameters from fixed literature values to variable measured values. By measuring and using the actual optical parameters of each patient's eye (corneal curvature radius, lens curvature radius, vitreous body curvature radius, refractive indices), the system achieves personalized precision without significantly increasing device complexity
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
This approach enables fast and accurate determination of tissue geometry for eye surgical lasers, reducing errors and computational burden, and allowing for more individualized and efficient tissue removal procedures.
Implementation Method 1
a corneal wavefront is determined from the corneal geometry by means of a physical model, wherein a change of an input wavefront upon a passage through the cornea with the ascertained corneal geometry is determined for ascertaining the corneal wavefront by means of the physical model
Implementation Method 2
a treatment apparatus for removing tissue of a human or animal eye by means of photodisruption and/or photoablation
Implementation Method 3
a treatment apparatus for removing tissue of a human or animal eye by means of photodisruption and/or photoablation
Data Source
AI summary
A method for providing control data for an eye surgical laser of a treatment apparatus for removing tissue is disclosed. The method includes utilizing a control device for determining a corneal geometry and an ocular wavefront of a human or animal eye from predetermined examination data. A corneal wavefront is then determined from the corneal geometry using a physical model, and an internal wavefront is calculated from a difference between the ocular wavefront and the corneal wavefront. A wavefront to be achieved is calculated from a difference of a preset target wavefront and the calculated internal wavefront. A target corneal geometry is determined from the wavefront to be achieved by the physical model, and a tissue geometry to be removed is calculated from a difference of the corneal geometry and the target corneal geometry, and control data for controlling the eye surgical laser is provided.