A Fusion Based Approach for Blood Vessel Segmentation from Fundus Images by Separating Brighter Optic Disc

2021 ◽  
Vol 31 (4) ◽  
pp. 811-820
Author(s):  
Farha Fatina Wahid ◽  
K. Sugandhi ◽  
G. Raju
Keyword(s):  
Blood Vessel ◽  
Optic Disc ◽  
Vessel Segmentation ◽  
Fundus Images ◽  
Blood Vessel Segmentation

scholarly journals Multi-Path Recurrent U-Net Segmentation of Retinal Fundus Image

2020 ◽  
Vol 10 (11) ◽  
pp. 3777 ◽  
Author(s):  
Yun Jiang ◽  
Falin Wang ◽  
Jing Gao ◽  
Simin Cao
Keyword(s):  
Blood Vessel ◽  
Optic Disc ◽  
Vessel Segmentation ◽  
Fundus Images ◽  
Fundus Image ◽  
Retinal Blood Vessel ◽  
Blood Vessel Segmentation ◽  
Optic Cup ◽  
Retinal Fundus Images ◽  
Retinal Fundus

Diabetes can induce diseases including diabetic retinopathy, cataracts, glaucoma, etc. The blindness caused by these diseases is irreversible. Early analysis of retinal fundus images, including optic disc and optic cup detection and retinal blood vessel segmentation, can effectively identify these diseases. The existing methods lack sufficient discrimination power for the fundus image and are easily affected by pathological regions. This paper proposes a novel multi-path recurrent U-Net architecture to achieve the segmentation of retinal fundus images. The effectiveness of the proposed network structure was proved by two segmentation tasks: optic disc and optic cup segmentation and retinal vessel segmentation. Our method achieved state-of-the-art results in the segmentation of the Drishti-GS1 dataset. Regarding optic disc segmentation, the accuracy and Dice values reached 0.9967 and 0.9817, respectively; as regards optic cup segmentation, the accuracy and Dice values reached 0.9950 and 0.8921, respectively. Our proposed method was also verified on the retinal blood vessel segmentation dataset DRIVE and achieved a good accuracy rate.

An unsupervised coarse-to-fine algorithm for blood vessel segmentation in fundus images

2017 ◽  
Vol 78 ◽  
pp. 182-192 ◽  
Author(s):  
Luiz Câmara Neto ◽  
Geraldo L.B. Ramalho ◽  
Jeová F.S. Rocha Neto ◽  
Rodrigo M.S. Veras ◽  
Fátima N.S. Medeiros
Keyword(s):  
Blood Vessel ◽  
Vessel Segmentation ◽  
Fundus Images ◽  
Blood Vessel Segmentation ◽  
Coarse To Fine

Blood vessel segmentation of fundus images via cross-modality dictionary learning

2018 ◽  
Vol 57 (25) ◽  
pp. 7287 ◽  
Author(s):  
Yan Yang ◽  
Feng Shao ◽  
Zhenqi Fu ◽  
Randi Fu
Keyword(s):  
Blood Vessel ◽  
Dictionary Learning ◽  
Vessel Segmentation ◽  
Fundus Images ◽  
Blood Vessel Segmentation
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