Paper
5 July 2024 Retina vessel segmentation based on dual encoder and edge detection
Jialu Zhao, Ruyun Chen
Author Affiliations +
Proceedings Volume 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024); 131844I (2024) https://doi.org/10.1117/12.3033156
Event: 3rd International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 2024, Kuala Lumpur, Malaysia
Abstract
In real-world medical scenarios, such as the diagnosis of diabetes, glaucoma, and liver surgeries, precise segmentation of blood vessels is required so that clinicians can more easily visualize abnormalities in the vessels and thus intervene in the early stages of the disease. Traditional computer-aided diagnosis methods have problems such as omission of edge information and spatial features of blood vessels, mislabeling of blood vessels, and low sensitivity of segmentation, so this project proposes a blood vessel segmentation model based on dual encoder-decoder with edge detection. The model captures the detail information of blood vessels to increase the accuracy of fine blood vessel segmentation, and increases the edge detection module and edge enhancement module, and uses knowledge distillation to improve the accuracy of edge detection. Through this research, it is proposed to solve the problems of existing blood vessel segmentation algorithms and design a high precision blood vessel segmentation model.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Jialu Zhao and Ruyun Chen "Retina vessel segmentation based on dual encoder and edge detection", Proc. SPIE 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 131844I (5 July 2024); https://doi.org/10.1117/12.3033156
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KEYWORDS
Blood vessels

Edge detection

Convolution

Data modeling

Vascular diseases

Image segmentation

Retina

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