# Quantitative Characterization of Corneal Collagen Architecture Using Intensity Gradient Modeling and Gaussian PDF Fitting

## TL;DR

This paper introduces a new method to study the organization of collagen in the cornea using image analysis and probability modeling.

## Contribution

A novel quantitative technique for analyzing corneal collagen organization using intensity gradient modeling and Gaussian PDF fitting is proposed.

## Key findings

- The method performs well in noisy or low-contrast conditions compared to traditional approaches like Fourier transform.
- It is applicable across species and healing stages, offering scalability and robustness.
- The technique is suitable for clinical diagnostics and treatment monitoring.

## Abstract

Background/Objectives: The transparency and biomechanical properties of the human cornea are governed by the precise organization of collagen fibers. A novel quantitative technique to analyze corneal collagen organization, based on intensity gradient modeling and probability density function (PDF) fitting, is proposed. Methods: Derived from second-harmonic generation (SHG) images, the method calculates image gradients, derives PDFs of gradient orientations, and fits them to Gaussian models. Results: Tested across species and temporal healing stages, this approach is an advantageous alternative to traditional methods like Fourier transform and structure tensor analyses, particularly in noisy or low-contrast conditions. Conclusions: The technique offers a scalable, robust framework suitable for research, clinical diagnostics, and treatment monitoring.