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Aug 2026

Deep Learning-based Automated Segmentation of Ultra-Widefield Retinal Vasculature for Cardiometabolic Disease Association Analysis.

This study establishes the first DL framework specifically designed for retinal vessel segmentation in true color UWF images and reveals disease-specific regional vascular patterns that would be missed by conventional fundus photography, highlighting the value of UWF imaging for comprehensive systemic disease assessmen...

Xinyue Wang, Xinyue Yang, Yu-Wei Wang et al. · 0 citations
Open access Aug 2026

Domain-Adaptive Retinal Vessel Segmentation for Unannotated Fundus Images

A domain-adaptive retinal vessel segmentation model (DA-VesselNet), a weakly supervised approach that transfers vessel-segmentation knowledge from annotated source datasets to the unannotated Retinal Fundus Multi-Disease Image Dataset (RFMiD), is proposed and applied to RFMiD, providing a structural resource for future...

M. Oladele, O. A. Alimi, O. Olugbara · 0 citations
Open access Aug 2026

Semantic Segmentation of Optical Coherence Tomography Images Based on TUnet+ Modeling

A lightweight TUnet+ network incorporating an innovatively designed PSE_C2fCIB module provides a robust technical foundation for automated diagnostic support and quantitative disease assessment, and it demonstrates the value of electromagnetic-wave imaging analysis in biomedical engineering.

Sheng Hu, Liang Li, Han Xiao · 0 citations
Jul 2026

ADF-Net: Adaptive Directional Feature Fusion Network for OCTA Vessel Segmentation.

An Adaptive Directional Feature Fusion Network (ADF-Net) is proposed for retinal vessel segmentation in OCTA images that integrates convolution-based local feature extraction and Swin Transformer-based global context modeling and effectively preserves vascular continuity and structural integrity for retinal vascular an...

Suxin Li, Idowu Paul Okuwobi · 0 citations
Conference Sep 2026

GA-Gabor guided swin-UNet for retinal vessel segmentation

Retinal vessel segmentation is a significant technique for assisting clinical diagnosis of fundus diseases. Although deep learning-based approaches have achieved significant progress in recent years, existing models still exhibit limitations in modeling high-frequency features of thin vessel structures, particularly in...

Lei Wang, D. A. Dewi, Ning-Rong Lai et al. · 0 citations
Open access Jul 2026

Retinal Blood Vessel Segmentation Using Attention V-Net with Scale-Aware Evaluation

Attention V-Net demonstrates consistent segmentation performance across vessel scales, and the scale-aware evaluation framework effectively reveals the performance gap between small and large vessel segmentation, providing a more clinically relevant assessment than conventional global evaluation for early diagnosis of...

H. Wijaya, Erwin Erwin, Annisa Darmawahyuni et al. · 0 citations

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