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Retinal blood vessels segmentation for ROP plus form diagnosis
| Autoři | |
|---|---|
| Rok publikování | 2025 |
| Druh | Kapitola v knize |
| Fakulta / Pracoviště MU | |
| Citace | |
| Popis | Eye diseases can have highly adverse outcomes without an early diagnosis and correct monitoring. Retinopathy of Prematurity (ROP) Plus Form, in particular, is a disease that can lead to childhood blindness, and its diagnosis requires medical experts to examine the retinal condition manually. Although developments in screening equipment have helped, this is still a time-consuming and subjective task. The development of automatic tools for Retinal Blood Vessel Segmentation allows the extraction of blood vessels from fundus images, which healthcare experts can then use to perform the diagnosis, monitoring, and prognosis of eye diseases. Thus, developing such a segmentation tool is a widely explored task with different methodologies that can be followed. However, many studies try to segment all the blood vessels rather than only the most important ones. In this work, we present a segmentation pipeline to segment only the main vessels whose characteristics can be used to assess ROP Plus Form disease. This pipeline uses different operations and filters, including CIELAB Enhancement, Background Normalization, Bell-Shaped Gaussian Matched Filtering, Modified Top-Hat operation, and Frangi Filtering. The final segmentation is done by determining a threshold value using the Triangle Threshold algorithm. The pipeline was tested in the well-known DRIVE Database, achieving an Accuracy of 0.949, Specificity of 0.963, and Sensitivity of 0.756. |