A Novel Ensemble Meta-Model for Enhanced Retinal Blood Vessel Segmentation Using Deep Learning Architectures
<b>Background:</b> Retinal blood vessel segmentation plays an important role in diagnosing retinal diseases such as diabetic retinopathy, glaucoma, and hypertensive retinopathy. Accurate segmentation of blood vessels in retinal images presents a challenging task due to noise, low contras...
Saved in:
Main Authors: | Mohamed Chetoui, Moulay A. Akhloufi |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
|
Series: | Biomedicines |
Subjects: | |
Online Access: | https://www.mdpi.com/2227-9059/13/1/141 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Sandpiper Optimization Algorithm With Region Growing Based Robust Retinal Blood Vessel Segmentation Approach
by: Ibrahim AlMohimeed, et al.
Published: (2024-01-01) -
Ensemble Learning for Three-dimensional Medical Image Segmentation of Organ at Risk in Brachytherapy Using Double U-Net, Bi-directional ConvLSTM U-Net, and Transformer Network
by: Soniya Pal, et al.
Published: (2024-12-01) -
MSM-TDE: multi-scale semantics mining and tiny details enhancement network for retinal vessel segmentation
by: Hongbin Zhang, et al.
Published: (2025-01-01) -
Performance and Efficiency Comparison of U-Net and Ghost U-Net in Road Crack Segmentation with Floating Point and Quantization Optimization
by: Haidhi Angkawijana Tedja, et al.
Published: (2024-12-01) -
An effective vessel segmentation method using SLOA-HGC
by: Zerui Liu, et al.
Published: (2025-01-01)