Retinal vessel segmentation using convolutional neural networks

Date

2018-05-05

Author

Ulusoy, İlkay

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Retinal vessel segmentation and extracting features such as tortuosity, width, length related to those vessels can be used in diagnosis, treatment and screening of many diseases such as retinopathy of prematurity, hypertension and diabetes. Therefore, automatic segmentation of vessels by computers will make the analysis of those diseases easier and will help during the screening, diagnosis and treatment processes. In this study, a solution based on convolutional neural networks (CNN) is proposed for automatic segmentation of retinal vessels. The proposed CNN model is tested on DRIVE dataset and a better performance than literature is achieved.

Subject Keywords

Image segmentation, Biomedical imaging, Blood vessels, Retinal vessels, Convolutional neural networks

URI

https://hdl.handle.net/11511/41526

DOI

https://doi.org/10.1109/siu.2018.8404262

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

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Citation Formats

İ. Ulusoy, “Retinal vessel segmentation using convolutional neural networks,” 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/41526.