Ophthalmological Laser Control Data via Eye Picture Analysis
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Solution Overview
Problem
Existing ophthalmological laser treatment apparatuses face challenges in accurately readjusting treatment positions after interruptions or inadequately performed pre-treatments, making it difficult to continue the treatment effectively.
Innovation Solution
The method involves using a camera device and a computing device to capture eye pictures, analyze phenomenological structures, and determine new treatment positions based on previously irradiated areas, allowing for precise planning and continuation of the treatment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If treatment positions are manually readjusted after interruption, then treatment can be continued, but treatment precision and planning accuracy deteriorate
Solution Approach 1:
The system captures eye pictures during treatment and uses image analysis algorithms to detect previously irradiated positions. This feedback mechanism allows the computing device to automatically adjust and plan subsequent treatment positions based on actual treatment progress, ensuring precision is maintained despite interruptions. The feedback loop closes by continuously comparing planned versus actual treatment positions and adapting the treatment plan accordingly.
Solution Approach 2:
The system performs preliminary capture of eye pictures and analysis of phenomenological structures before finalizing treatment positions. By pre-analyzing the eye structure and predicting treatment outcomes, the system can prepare adjusted treatment plans in advance, ensuring that even if treatment is interrupted, the next phase can be immediately resumed with correct positioning without manual readjustment.
2Reliability
If treatment is interrupted for any reason, then patient safety can be prioritized, but treatment planning and resumption become difficult
Solution Approach 1:
The system continuously monitors treatment progress by capturing eye pictures and analyzing them to detect irradiated positions. When treatment is interrupted, this feedback information is preserved and automatically used to generate resumption plans. The computing device uses the stored eye pictures and treatment data to automatically reconstruct the treatment plan, making resumption straightforward and maintaining both safety and ease of operation.
Solution Approach 2:
The system performs preliminary capture and analysis of eye structures before treatment begins and continuously updates this data during treatment. This preliminary preparation ensures that when treatment is interrupted for safety reasons, all necessary information is already available to immediately resume treatment without requiring manual readjustment or re-planning, thus maintaining both patient safety and operational ease.
3Ease of manufacture
If treatment positions are planned without considering previous irradiated areas, then treatment planning is simple, but treatment completeness deteriorates
Solution Approach 1:
The system uses image analysis algorithms to detect previously irradiated positions from captured eye pictures and feeds this information back into the treatment planning process. This feedback mechanism automatically adjusts subsequent treatment plans to avoid redundant irradiation of treated areas while ensuring complete coverage of untreated areas, maintaining both planning simplicity and treatment completeness through automated adaptation.
Solution Approach 2:
The system performs preliminary analysis of eye structures and treatment areas before finalizing the treatment plan. By pre-identifying phenomological structures and predicting treatment outcomes, the system automatically generates comprehensive treatment plans that account for previous irradiated areas, ensuring treatment completeness is achieved automatically without complicating the planning process.
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 more accurate planning of treatment positions, improving the overall effectiveness and completeness of ophthalmological laser treatments, even after interruptions or inadequate pre-treatments.
Implementation Method 1
acquiring at least one eye picture of an eye by a camera device
Implementation Method 2
laser pulses effect a photodisruption and/or ablation, in particular a plasma-assisted ablation, in a focus situated within the organic tissue
Implementation Method 3
laser pulses effect a photodisruption and/or ablation
Data Source
AI summary
The invention relates to a treatment apparatus (10) and to a method for providing control data for an ophthalmological laser (12) of a treatment apparatus (10). The method incudes capturing (S10) at least one eye picture of an eye (16) by a camera device (28); ascertaining (S12) phenomenological structures (24) of the eye (16) from the eye picture by a computing device (18), wherein the computing device (18) determines the phenomenological structures (24) by an image analysis algorithm; ascertaining (S14) treatment positions (26) in the eye for the treatment with the ophthalmological laser (12) depending on the phenomenological structures (24) by the computing device (18); and providing (S16) control data for the treatment apparatus (10) by the computing device (18), which includes the treatment positions (26) in the eye (16) for the treatment.