A retinal vessel segmentation network fusing cross-modal features

IF 0.4 4区 计算机科学 Q4 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Ieice Transactions on Fundamentals of Electronics Communications and Computer Sciences Pub Date : 2023-01-01 DOI:10.1587/transfun.2023eal2063
Xiaosheng YU, Jianning CHI, Ming XU
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Abstract

Accurate segmentation of fundus vessel structure can effectively assist doctors in diagnosing eye diseases. In this paper, we propose a fundus blood vessel segmentation network combined with cross-modal features and verify our method on the public data set OCTA-500. Experimental results show that our method has high accuracy and robustness.
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融合跨模态特征的视网膜血管分割网络
眼底血管结构的准确分割可以有效地辅助医生诊断眼病。本文提出了一种结合跨模态特征的眼底血管分割网络,并在公开数据集OCTA-500上验证了我们的方法。实验结果表明,该方法具有较高的准确性和鲁棒性。
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来源期刊
CiteScore
1.10
自引率
20.00%
发文量
137
审稿时长
3.9 months
期刊介绍: Includes reports on research, developments, and examinations performed by the Society''s members for the specific fields shown in the category list such as detailed below, the contents of which may advance the development of science and industry: (1) Reports on new theories, experiments with new contents, or extensions of and supplements to conventional theories and experiments. (2) Reports on development of measurement technology and various applied technologies. (3) Reports on the planning, design, manufacture, testing, or operation of facilities, machinery, parts, materials, etc. (4) Presentation of new methods, suggestion of new angles, ideas, systematization, software, or any new facts regarding the above.
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