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Lipid Layer Interferometry (LLI)

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Understanding Lipid Layer Interferometry (LLI)

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Lipid Layer Interferometry (LLI) is an optical technique used to measure the thickness and quality of the tear film’s lipid layer, which is essential for maintaining eye health. This method relies on light interference principles to evaluate lipid layer characteristics in real-time.

Widely adopted in ophthalmology for both clinical diagnostics and research, LLI offers a non-invasive approach to monitor tear film dynamics. The lipid layer forms a protective barrier that reduces tear evaporation, a major contributor to Dry Eye Disease (DED). LLI plays a crucial role in diagnosing conditions such as DED by providing objective insights into tear film stability.

Challenges in Lipid Layer Interferometry

Despite its clinical value, LLI faces several challenges in effective implementation and interpretation

Lipid Layer Interferometry chalenges

Challenges in Lipid Layer Interferometry

Lipid Layer Interferometry chalenges

Despite its clinical value, LLI faces several challenges in effective implementation and interpretation

FH-POISE and Lipid Layer Interferometry

FH-POISE enhances the detection and analysis of tear film abnormalities by integrating advanced ophthalmic imaging with integrated insights. This solution facilitates objective, reproducible assessments of lipid layer dynamics, supporting accurate diagnosis and personalized treatment planning.

How FH-POISE Supports Lipid Layer Interferometry:

Integrated Blink Parsing

Integrated Blink Parsing

Analyzes video sequences captured under specialized illumination to detect blink frequency, inter-blink duration, and tear film stability.

Interference Pattern Analysis

Interference Pattern Analysis

Uses deep-learning models to assess every frame of the video, identifying subtle changes in lipid layer integrity.

Objective Metrics

Objective Metrics

Provides quantitative data, including lipid layer thickness and grading based on established scales (e.g., Yokoi reference), helping clinicians make informed treatment decisions.

Enhanced Diagnostic Confidence: Delivers comprehensive, AI-generated reports that standardize LLI interpretation, reducing variability and improving diagnostic reliability.

FH-POISE combines advanced analysis with specialized imaging to help clinicians detect and manage Dry Eye Disease with precise, reproducible assessments.

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