RBAD: A Dataset and Benchmark for Retinal Vessels Branching Angle Detection
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866916328096399360 |
|---|---|
| author | Wang, Hao Zhu, Wenhui Qin, Jiayou Li, Xin Dumitrascu, Oana Chen, Xiwen Qiu, Peijie Razi, Abolfazl |
| author_facet | Wang, Hao Zhu, Wenhui Qin, Jiayou Li, Xin Dumitrascu, Oana Chen, Xiwen Qiu, Peijie Razi, Abolfazl |
| contents | Detecting retinal image analysis, particularly the geometrical features of branching points, plays an essential role in diagnosing eye diseases. However, existing methods used for this purpose often are coarse-level and lack fine-grained analysis for efficient annotation. To mitigate these issues, this paper proposes a novel method for detecting retinal branching angles using a self-configured image processing technique. Additionally, we offer an open-source annotation tool and a benchmark dataset comprising 40 images annotated with retinal branching angles. Our methodology for retinal branching angle detection and calculation is detailed, followed by a benchmark analysis comparing our method with previous approaches. The results indicate that our method is robust under various conditions with high accuracy and efficiency, which offers a valuable instrument for ophthalmic research and clinical applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_12271 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | RBAD: A Dataset and Benchmark for Retinal Vessels Branching Angle Detection Wang, Hao Zhu, Wenhui Qin, Jiayou Li, Xin Dumitrascu, Oana Chen, Xiwen Qiu, Peijie Razi, Abolfazl Computer Vision and Pattern Recognition Image and Video Processing Detecting retinal image analysis, particularly the geometrical features of branching points, plays an essential role in diagnosing eye diseases. However, existing methods used for this purpose often are coarse-level and lack fine-grained analysis for efficient annotation. To mitigate these issues, this paper proposes a novel method for detecting retinal branching angles using a self-configured image processing technique. Additionally, we offer an open-source annotation tool and a benchmark dataset comprising 40 images annotated with retinal branching angles. Our methodology for retinal branching angle detection and calculation is detailed, followed by a benchmark analysis comparing our method with previous approaches. The results indicate that our method is robust under various conditions with high accuracy and efficiency, which offers a valuable instrument for ophthalmic research and clinical applications. |
| title | RBAD: A Dataset and Benchmark for Retinal Vessels Branching Angle Detection |
| topic | Computer Vision and Pattern Recognition Image and Video Processing |
| url | https://arxiv.org/abs/2407.12271 |