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Low rank based FAZ segmentation in OCTA images.

Farnaz Sedighin¹, Fatemeh Rezaei², Maryam Monemian²

¹Medical Image and Signal Processing Research Center, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, 8174673461, Iran. f.sedighin@amt.mui.ac.ir.

Scientific Reports

|July 9, 2025

Summary

This study introduces novel methods for segmenting the Fovea Avascular Zone (FAZ) in Optical Coherence Tomography Angiography (OCTA) images. Accurate FAZ segmentation aids in diagnosing eye diseases by analyzing retinal vascular changes.

Keywords:

FAZ segmentation Low-rank estimation Optical coherence tomography angiography Tensor ring decomposition

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Area of Science:

Ophthalmology
Medical Imaging
Biomedical Engineering

Background:

Optical Coherence Tomography Angiography (OCTA) is a key non-invasive technique for retinal vascular imaging.
Retinal diseases can alter vascular density and the Fovea Avascular Zone (FAZ) morphology.
FAZ analysis is crucial for diagnosing various eye conditions.

Purpose of the Study:

To develop and evaluate novel methods for accurate FAZ segmentation in OCTA images.
To improve the diagnosis of eye diseases through precise FAZ analysis.
To introduce low-rank Tensor Ring (TR) decomposition for FAZ segmentation.

Main Methods:

Proposed a three-step approach for FAZ segmentation: localization, de-noising, and refinement.
Employed two FAZ localization techniques: Low-rank Tensor Ring (TR) decomposition and morphological operators.
Utilized de-noised OCTA images and FAZ localization information for segmentation.

Main Results:

Achieved accurate segmentation of the Fovea Avascular Zone (FAZ) from OCTA images.
Demonstrated the effectiveness of the proposed methods, including the novel use of low-rank TR estimation.
Simulation results validated the performance of the segmentation techniques.

Conclusions:

The proposed methods offer accurate FAZ segmentation from OCTA images.
Low-rank TR decomposition is a novel and effective approach for FAZ segmentation.
Accurate FAZ segmentation can significantly aid in the early diagnosis of retinal diseases.