# Comprehensive and Region-Specific Retinal Health Assessment Using Phasor Analysis of Multispectral Images and Machine Learning

## TL;DR

This paper shows that combining phasor analysis of multispectral images with machine learning improves retinal disease classification compared to traditional methods.

## Contribution

The study introduces phasor analysis as a superior dimensionality reduction method for retinal health assessment using multispectral imaging.

## Key findings

- Phasor analysis outperforms average reflectance values in classifying retinal health.
- Multispectral images provide better classification accuracy than RGB-like images derived from them.
- Analyzing the entire retina improves classification performance due to widespread disease effects.

## Abstract

This study examines the efficacy of phasor analysis in distinguishing between healthy and diseased retinas using multispectral imaging data together with machine learning approaches. Our results demonstrate that phasor analysis of multispectral images surpasses average reflectance values in classification performance, serving as an effective dimensionality reduction technique to extract essential features, with the first harmonic yielding optimal results when paired with Z-score normalization. To compare the effectiveness of multispectral images with that of a conventional color fundus camera, we extracted three spectral bands corresponding to the red, green, and blue regions and combined them to create RGB-like images, which were then subjected to the same analysis. Our study found that phasor analysis of multispectral images provided more accurate classification results than phasor analysis of RGB-like images. An examination of different regions of interest showed that using the entire retina yields the best classification performance, likely due to the advanced stage of the diseases, which had progressed to affect the entire fundus. Our findings suggest that phasor analysis of multispectral images and machine learning are a powerful tools for retinal disease classification.