Statistical modeling of corneal OCT speckle. A distributional model-free approach

TL;DR

This paper proposes a distributional model-free approach for modeling corneal OCT speckle, which outperforms traditional distributional models and should be considered as a first step in speckle analysis.

Contribution

It introduces a novel, simple, distributional model-free method for speckle analysis in OCT, challenging the reliance on parametric models.

Findings

The model-free approach outperforms fitted distributional models in experiments.

It is effective across phantom, ex-vivo, and in-vivo corneal OCT data.

The method is simple and practical for clinical applications.

Abstract

In biomedical optics, it is often of interest to statistically model the amplitude of the speckle using some distributional models with their parameters acting as biomarkers. In this paper, a paradigm shift is being advocated in which a distributional model-free approach is used. Specifically, a range of distances, evaluated in different domains, between an empirical nonparametric distribution of the normalized speckle amplitude sample and the benchmark Rayleigh distribution, is considered. Using OCT images from phantoms, two ex-vivo experiments with porcine corneas and an in-vivo experiment with human corneas, an evidence is provided that the distributional model-free approach, despite its simplicity, could lead to better results than the best-fitted (among a range of considered models) distributional model. Concluding, in practice, the distributional model-free approach should be considered as the first choice to speckle modeling before a distributional-based approach is utilized.