A Fundus Image Dataset for AI-based Artery-Vein Vessel Segmentation
Abstract Retinal artery-vein vessels are associated with systemic chronic diseases and cardiovascular diseases. Therefore, the accurate quantitative analysis of retinal artery-vein vessels is the preliminary basis of clinical diagnosis. Most of the existing artificial intelligence(AI) methods are da...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-05381-2 |
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| _version_ | 1849344018105761792 |
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| author | Zhuo Deng Weihao Gao Zheng Gong Run Gan Lu Chen Shaochong Zhang Lan Ma |
| author_facet | Zhuo Deng Weihao Gao Zheng Gong Run Gan Lu Chen Shaochong Zhang Lan Ma |
| author_sort | Zhuo Deng |
| collection | DOAJ |
| description | Abstract Retinal artery-vein vessels are associated with systemic chronic diseases and cardiovascular diseases. Therefore, the accurate quantitative analysis of retinal artery-vein vessels is the preliminary basis of clinical diagnosis. Most of the existing artificial intelligence(AI) methods are data-driven. Although some public retinal artery-vein vessel segmentation datasets have been released, their data quality is unsatisfactory. In this paper, we establish a new fundus image dataset for AI-based artery-vein segmentation, Fundus-AVSeg. It consists of 100 high-resolution fundus images with pixel-wise manual annotation by professional ophthalmologists. We believe our Fundus-AVSeg will benefit the further development of retinal artery-vein vessel segmentation. |
| format | Article |
| id | doaj-art-a9c1310bdd9e4c58852f473151aa41df |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-a9c1310bdd9e4c58852f473151aa41df2025-08-20T03:42:47ZengNature PortfolioScientific Data2052-44632025-07-011211810.1038/s41597-025-05381-2A Fundus Image Dataset for AI-based Artery-Vein Vessel SegmentationZhuo Deng0Weihao Gao1Zheng Gong2Run Gan3Lu Chen4Shaochong Zhang5Lan Ma6Shenzhen International Graduate School, Tsinghua UniversityShenzhen International Graduate School, Tsinghua UniversityShenzhen International Graduate School, Tsinghua UniversityThe Shenzhen Eye HospitalThe Shenzhen Eye HospitalThe Shenzhen Eye HospitalShenzhen International Graduate School, Tsinghua UniversityAbstract Retinal artery-vein vessels are associated with systemic chronic diseases and cardiovascular diseases. Therefore, the accurate quantitative analysis of retinal artery-vein vessels is the preliminary basis of clinical diagnosis. Most of the existing artificial intelligence(AI) methods are data-driven. Although some public retinal artery-vein vessel segmentation datasets have been released, their data quality is unsatisfactory. In this paper, we establish a new fundus image dataset for AI-based artery-vein segmentation, Fundus-AVSeg. It consists of 100 high-resolution fundus images with pixel-wise manual annotation by professional ophthalmologists. We believe our Fundus-AVSeg will benefit the further development of retinal artery-vein vessel segmentation.https://doi.org/10.1038/s41597-025-05381-2 |
| spellingShingle | Zhuo Deng Weihao Gao Zheng Gong Run Gan Lu Chen Shaochong Zhang Lan Ma A Fundus Image Dataset for AI-based Artery-Vein Vessel Segmentation Scientific Data |
| title | A Fundus Image Dataset for AI-based Artery-Vein Vessel Segmentation |
| title_full | A Fundus Image Dataset for AI-based Artery-Vein Vessel Segmentation |
| title_fullStr | A Fundus Image Dataset for AI-based Artery-Vein Vessel Segmentation |
| title_full_unstemmed | A Fundus Image Dataset for AI-based Artery-Vein Vessel Segmentation |
| title_short | A Fundus Image Dataset for AI-based Artery-Vein Vessel Segmentation |
| title_sort | fundus image dataset for ai based artery vein vessel segmentation |
| url | https://doi.org/10.1038/s41597-025-05381-2 |
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