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IMCS/Publications/CSJM/Issues/CSJM v.34, n1. (100), 2026/

VasFAZ-Net: A Hybrid Loss-Optimized EfficientNet-scSE Network for Retinal Vasculature and FAZ Segmentation in OCTA

Authors: Nisan Pranavah Raja, Varun P. Gopi, Bibin Francis, Chelli Devi N
Keywords: Optical coherence tomography angiography (OCTA), automated retinal segmentation, deep learning, spatial–channel attention, foveal avascular zone (FAZ), retinal microvasculature.

Abstract

Accurate segmentation of fine retinal vessels and the Foveal Avascular Zone (FAZ) in OCTA images remains challenging due to low contrast, noise, and class imbalance. To address this, a lightweight deep learning framework called VasFAZ-Net is proposed, which uses an EfficientNet-B0 encoder, a parallel spatial and channel squeeze-and-excitation (scSE) decoder, and a hybrid Dice–Focal loss function, trained on the OCTA-500 dataset with both 3 mm and 6 mm scans. The proposed model achieved Dice scores of up to 88.48\% for vessel segmentation and 97.98\% for FAZ segmentation with only 8.8 million parameters and an inference time of 18.2 ms per image. These results demonstrate that the proposed method provides accurate, computationally efficient, and clinically deployable multi-target OCTA segmentation for retinal disease analysis.

Nisan Pranavah Raja
ORCID: https://orcid.org/0009-0006-4518-6787
National Institute of Technology Tiruchirappalli
Department of Electronics and Communication Engineering, National Institute of
Technology Tiruchirappalli, Tamil Nadu-620015, India.
E-mail:

Varun P. Gopi
ORCID: https://orcid.org/0000-0001-5593-3949
National Institute of Technology Tiruchirappalli
Department of Electronics and Communication Engineering, National Institute of
Technology Tiruchirappalli, Tamil Nadu-620015, India.
E-mail:

Bibin Francis
ORCID: https://orcid.org/0000-0002-9828-6443
National Institute of Technology Tiruchirappalli
Department of Electronics and Communication Engineering, National Institute of
Technology Tiruchirappalli, Tamil Nadu-620015, India.
E-mail:

Chelli Devi N
ORCID: https://orcid.org/0000-0002-3430-7428
Department of Biomedical Engineering, Kalasalingam Academy of Research and
Education
Kalasalingam Academy of Research and Education, Krishnankoil, 620015, Tamil
Nadu, India
E-mail:

DOI

https://doi.org/10.56415/csjm.v34.01

Fulltext

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