Segmentation of Laser Marks of Diabetic Retinopathy in the Fundus Photographs Using Lightweight U-Net
Diabetic retinopathy (DR) is a prevalent vision-threatening disease worldwide. Laser marks are the scars left after panretinal photocoagulation, a treatment to prevent patients with severe DR from losing vision. In this study, we develop a deep learning algorithm based on the lightweight U-Net to se...
Saved in:
Main Authors: | Yukang Jiang, Jianying Pan, Ming Yuan, Yanhe Shen, Jin Zhu, Yishen Wang, Yewei Li, Ke Zhang, Qingyun Yu, Huirui Xie, Huiting Li, Xueqin Wang, Yan Luo |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2021-01-01
|
Series: | Journal of Diabetes Research |
Online Access: | http://dx.doi.org/10.1155/2021/8766517 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Quantitative evaluation of the wide-field fundus photographs in eyes with severe stage 3 and stage 4A retinopathy of prematurity
by: Sadik Etka Bayramoglu, et al.
Published: (2025-01-01) -
FundusNet: A Deep-Learning Approach for Fast Diagnosis of Neurodegenerative and Eye Diseases Using Fundus Images
by: Wenxing Hu, et al.
Published: (2025-01-01) -
LDDP-Net: A Lightweight Neural Network with Dual Decoding Paths for Defect Segmentation of LED Chips
by: Jie Zhang, et al.
Published: (2025-01-01) -
Identification of diabetic retinopathy lesions in fundus images by integrating CNN and vision mamba models.
by: Zenglei Liu, et al.
Published: (2025-01-01) -
MLHI-Net: multi-level hybrid lightweight water body segmentation network for urban shoreline detection
by: Jianhua Ye, et al.
Published: (2025-02-01)