AI for Retinal Vessels Segmentation

Abstract:

Diabetes is a common disease in the modern life. According to WHO’s data, in 2018, there were 8.3% of adult population had diabetes. Many countries over the world have spent a lot of finance, force to treat this disease. One of the most dangerous complications that diabetes can cause is the blood vessel lesions. In the following works, we perform:

• Blood vessels segmentation with image processing tools [1], machine learning classifiers [2], and deep learning methods [3]

• Optical disc segmentation

• Vessel enhancement

• etc...

Automatic Segmentation Results [2]

Row-wise: Input, Segmentation

TBA

Reference:

[1] D. N. H. Thanh, S. Dvoenko, V. B. S. Prasath, N. H. Hai. Blood vessels segmentation method for retinal fundus images based on adaptive principal curvature and image derivative operators. Third International Workshop on Photogrammetric and Computer Vision Techniques for Video surveillance, Biometrics and Biomedicine (PSBB), Moscow, Russia, May 2019. Proc. ISPRS International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-2/W12, 211-218, May 2019. doi:10.5194/isprs-archives-XLII-2-W12-211-2019

[2] V. B. S. Prasath et al. RFRET-Random forests for retinal vessel segmentation. In preparation, 2025.

[3] V. B. S. Prasath et al. TBA. In preparation, 2025.

MS Thesis:

Harshith Bondada. Retinal Vessel Segmentation on Ultra Wide-field Fluorescein Angiography Images. MS Thesis, Electrical Engineering and Computer Science, University of Cincinnati, USA, 2019.

Related Works:

Denoising and Segmentation of vessel structures from microscopy images.

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