Tool Tip Positioning Relative to Eye Tissue Using Reference Markers
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Solution Overview
Problem
Current ophthalmological surgical procedures face challenges in accurately determining the position and orientation of tools relative to transparent and fragile eye tissues, such as the cornea and posterior capsule, due to low visibility and optical distortions, which can lead to tissue damage and complications during surgeries like cataract removal.
Innovation Solution
A system and method utilizing a 3D imager and processor to track the position and orientation of a tool relative to eye tissues by acquiring images of tissue reference markers, such as the iris, and using pre-determined 3D models to calculate the relative position and orientation of the tool tip to the eye tissue of interest, providing real-time feedback to prevent damage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If a stereoscopic microscope is used for ophthalmological surgery, then the surgeon can perform common procedures, but the transparent eye tissues are difficult to see due to low visibility
Solution Approach 1:
The system overlays color-coded virtual boundary indicators on the microscopic video feed to represent different tissue boundaries and safety zones. These visual enhancements transform the invisible or faint transparent tissues into clearly distinguishable colored regions, allowing surgeons to identify tissue boundaries and maintain safe distances without direct visual contact with the transparent structures.
Solution Approach 2:
The system introduces an intermediary computational layer that processes microscope video feed, integrates OCT scan data, and generates virtual boundary representations. This intermediary system acts as a mediator between the surgeon and the transparent tissues, providing indirect visual information about tissue locations and boundaries that cannot be directly observed through the microscope alone.
2Measurement precision
If the surgeon relies on visual observation through the microscope, then the procedure can be performed, but accurate incision and positioning are difficult due to optical distortions and low contrast
Solution Approach 1:
The system merges multiple data sources including microscope video feed, OCT scan data, and tool tracker information into a single integrated visualization. This combination allows the system to compensate for the limitations of individual methods, providing accurate tool positioning and tissue boundary identification without requiring the surgeon to manually process multiple separate data streams.
Solution Approach 2:
The system provides real-time feedback by continuously updating virtual boundary indicators based on tool position and tissue location. As the tool moves, the system recalculates and refreshes the displayed boundaries and safety zones, giving the surgeon immediate feedback on the relative positions of the tool and tissues to prevent damage.
3Loss of information
If non-visual scanning technologies are used to locate eye capsule, then additional guidance on distance can be provided, but the system requires integration of multiple data sources increasing complexity
Solution Approach 1:
The system employs a multi-functional platform that handles microscope video acquisition, OCT data processing, tool tracking, boundary calculation, and visualization through a single integrated architecture. This universal system performs multiple functions simultaneously, reducing the need for separate independent systems and simplifying the overall complexity despite the sophisticated data integration required.
Data Source
AI summary
System for determining a position of a tool-point-of-interest of a tool, relative to an eye-tissue-of-interest, which includes and imager a tool-tracker and a processor. The imager acquires an image of a tissue-reference-marker. The tool-tracker determines information relating to the P&O of the tool in a reference-coordinate-system. The imager and the tool-tracker are in registration with the reference-coordinate-system. The processor determines the position of the tissue-reference-marker in the reference-coordinate-system, according to the acquired image of the tissue-reference-marker. The processor determines the P&O of the eye-tissue-of-interest in the reference-coordinate-system according to at least the position of the tissue-reference-marker and a relative position between the tissue-reference-marker and the eye-tissue-of-interest. The relative position is pre-determined from a stored-3D-model. The processor determines the position of a tool-point-of-interest in the reference-coordinate-system from the P&O of the tool in the reference-coordinate-system. The processor also determines a relative position between the tool-point-of-interest and the eye-tissue-of-interest.