DUNet: A deformable network for retinal vessel segmentation

Automatic segmentation of retinal vessels in fundus images plays an important role in the diagnosis of some diseases such as diabetes and hypertension. In this paper, we propose Deformable U-Net (DUNet), which exploits the retinal vessels’ local features with a U-shape architecture, in an end to end...

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Bibliographic Details
Published in:	Knowledge-based systems Vol. 178; pp. 149 - 162
Main Authors:	Jin, Qiangguo, Meng, Zhaopeng, Pham, Tuan D., Chen, Qi, Wei, Leyi, Su, Ran
Format:	Journal Article
Language:	English
Published:	Amsterdam Elsevier B.V 15.08.2019 Elsevier Science Ltd
Subjects:	Blood vessels Convolution Deformable convolution Deformation Diabetes Diagnosis Disease DUNet Feature extraction Formability Hypertension Image segmentation Localization Medical diagnosis Networks Neural networks Operators Retinal blood vessel Segmentation U-Net DUNet Segmentation Retinal blood vessel U-Net Deformable convolution
ISSN:	0950-7051, 1872-7409, 1872-7409
Online Access:	Get full text
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