A Method for Retina Segmentation by Means of U-Net Network

被引:0
|
作者
Santone, Antonella [1 ]
De Vivo, Rosamaria [1 ]
Recchia, Laura [1 ]
Cesarelli, Mario [2 ]
Mercaldo, Francesco [1 ]
机构
[1] Univ Molise, Dept Med & Hlth Sci Vincenzo Tiberio, I-86100 Campobasso, Italy
[2] Univ Sannio, Dept Engn, I-82100 Benevento, Italy
关键词
retina; deep learning; segmentation; U-Net; healthcare;
D O I
10.3390/electronics13224340
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Retinal image segmentation plays a critical role in diagnosing and monitoring ophthalmic diseases such as diabetic retinopathy and age-related macular degeneration. We propose a deep learning-based approach utilizing the U-Net network for the accurate and efficient segmentation of retinal images. U-Net, a convolutional neural network widely used for its performance in medical image segmentation, is employed to segment key retinal structures, including the optic disc and blood vessels. We evaluate the proposed model on a publicly available retinal image dataset, demonstrating interesting performance in automatic retina segmentation, thus showing the effectiveness of the proposed method. Our proposal provides a promising method for automated retinal image analysis, aiding in early disease detection and personalized treatment planning.
引用
收藏
页数:16
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