Post-operative Iris Color Prediction Using Anatomical Feature Analysis
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Solution Overview
Problem
Current laser iris color-change procedures face challenges in accurately predicting the post-operative iris color due to the occlusion of stromal fibers by pigment, which can lead to sectoral heterochromia if the procedure is not completed.
Innovation Solution
The method involves identifying and measuring various anatomical features of the patient's eye using specialized imaging and measurement devices, compiling a database of these measurements and their associated iris colors, and comparing the patient's measurements to predict the post-operative iris color.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a small area of the iris is treated to test the outcome, then the patient can avoid permanent discoloration by not proceeding with the full procedure, but the prediction accuracy is insufficient because a relatively large area of stromal fiber exposure is required to generate sufficient backscatter
Solution Approach 1:
The system creates a digital copy or simulation of the iris by capturing images and using computational algorithms to predict the post-operative appearance. This virtual model allows accurate prediction without physically treating the actual iris, eliminating the risk of permanent discoloration while maintaining prediction accuracy.
Solution Approach 2:
A computational algorithm acts as an intermediary between the patient's current iris appearance and the predicted post-operative result. The algorithm processes captured images and simulates the laser treatment effects, providing accurate predictions without requiring actual tissue exposure or backscatter generation.
2Adaptability or versatility
If the stromal pigment is reduced and/or eliminated using electromagnetic radiation, then the perceived iris color changes to reveal the underlying blue or green iris, but the ability to predict the outcome is compromised due to occlusion of stromal fibers by pigment
Solution Approach 1:
The system performs preliminary actions by capturing images of the iris before treatment and using computational algorithms to simulate the expected outcome. This allows accurate prediction of the color change without actually reducing the stromal pigment, thereby maintaining measurement precision while preserving the ability to predict outcomes.
Solution Approach 2:
The patent replaces the physical/optical mechanism of light backscatter through treated stromal fibers with a computational simulation system. Instead of relying on actual light interaction with modified tissue, the system uses image processing and algorithms to predict the appearance, eliminating the occlusion problem while maintaining prediction accuracy.
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 allows for a reasonably accurate prediction of the patient's iris color after the procedure, effectively managing patient expectations and avoiding permanent discoloration.
Implementation Method 1
applying electromagnetic radiation to the anterior iris surface, thereby initiating the reduction and/or elimination of the stromal pigment
Implementation Method 2
the visible light entering the iris is scattered by the gray iris fibers into the light's various wavelengths (i.e., colors or, more specifically, hues)
Implementation Method 3
The longer wavelengths (red, orange, yellow, and, in some cases, green) are absorbed by the thick layer of pigment on the back of the iris (known as the Iris pigment epithelium or 'IPE')
Data Source
AI summary
The present invention predicts prior to a laser iris color-change procedure what a patient's iris color will be after the procedure. The present invention does so by identifying and measuring a variety of anatomical features of the patient's eye that affect or are otherwise relevant to predicting the patient's post-operative iris color, translating these measurements into a post-operative iris color prediction, and communicating this prediction to the patient in a manner sufficient to manage the patient's expectations with respect to the aesthetic outcome of the procedure.