Retinal Membrane Visualization via Image Processing
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Solution Overview
Problem
Membrane peeling in the eye is challenging due to poor visibility of the epiretinal membrane using traditional microscopes, and existing dyes are toxic and provide low color contrast, making it difficult for surgeons to differentiate the membrane from surrounding tissue effectively.
Innovation Solution
A method involving the recording of pre- and post-staining images of the retina, applying image processing to identify and highlight the membrane regions, and using a surgical microscope with optics, camera, and display to enhance visibility by transforming images to align corresponding structures and presenting highlighted membrane areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If traditional dyes are used to stain the epiretinal membrane, then the membrane becomes visible, but the dyes are toxic and provide low color contrast
Solution Approach 1:
The patent uses a non-toxic blue dye applied to the internal limiting membrane as an intermediary marker. This blue-stained membrane serves as a reference structure that helps the surgeon indirectly locate and visualize the epiretinal membrane through image processing, avoiding direct staining of the target membrane with toxic dyes
Solution Approach 2:
The patent creates a digital copy of the retinal image and processes it computationally to enhance membrane visibility. By recording images before and after staining and applying image processing algorithms, the system generates an enhanced visualization of the membrane without requiring high concentrations of toxic dyes
2Object-affected harmful factors
If dyes are used with high dilution to reduce toxicity, then toxic effects are minimized, but color contrast decreases and membrane visibility worsens
Solution Approach 1:
The system creates digital copies of the stained retinal image and applies image processing enhancement algorithms. This allows the use of highly diluted non-toxic dyes while compensating for the reduced color contrast through computational image processing that highlights the membrane structure
Solution Approach 2:
The patent replaces the reliance on optical contrast from concentrated dyes with a computational image processing system. Instead of depending on the mechanical/optical properties of high-concentration dyes, the system uses digital image analysis to enhance visibility, allowing substitution of toxic concentrated dyes with non-toxic diluted alternatives
3Productivity
If the epiretinal membrane is peeled off using traditional microscopy, then the membrane can be removed, but the poor visibility makes the procedure difficult and time-consuming
Solution Approach 1:
The patent applies the blue staining and performs image processing enhancement before the actual membrane peeling procedure. By pre-visualizing the membrane location and extent through the enhanced imaging system, the surgeon can plan the peeling procedure more efficiently and perform it with better visibility throughout the operation
Solution Approach 2:
The system uses digital copying and processing of retinal images to create an enhanced visualization overlay that guides the surgical procedure. This digital representation allows the surgeon to see the membrane clearly without increasing physical magnification or requiring prolonged surgical time
Data Source
AI summary
A method for visualizing a membrane on a retina of an eye includes recording a first image of the retina of the eye, wherein the membrane on the retina of the eye is not stained, recording a second image of the retina of the eye after the membrane on the retina of the eye has been stained, determining a first transformation such that mutually corresponding structures of the retina of the eye are located at mutually corresponding places in the second image and in the first image which was transformed with the first transformation, identifying image regions in the second image, which contain the membrane on the retina, based on the transformed first image and the recorded second image, and displaying the second image such that the identified image regions in the second image are highlighted relative to the surroundings of the identified image regions.