RBAD: A Dataset and Benchmark for Retinal Vessels Branching Angle Detection

• URL: http://arxiv.org/abs/2407.12271v1
• Date: Wed, 17 Jul 2024 02:37:39 GMT
• Title: RBAD: A Dataset and Benchmark for Retinal Vessels Branching Angle Detection
• Authors: Hao Wang, Wenhui Zhu, Jiayou Qin, Xin Li, Oana Dumitrascu, Xiwen Chen, Peijie Qiu, Abolfazl Razi,
• Abstract summary: This paper proposes a novel method for detecting retinal branching angles using a self-configured image processing technique. We offer an open-source annotation tool and a benchmark dataset comprising 40 images annotated with retinal branching angles.
• Score: 6.671669971067487
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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