An improved U-net architecture for simultaneous arteriole and venule segmentation in fundus image

Xiayu Xu, Tao Tan, Feng Xu

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

7 Citaten (Scopus)

Samenvatting

The segmentation and classification of retinal arterioles and venules play an important role in the diagnosis of various eye diseases and systemic diseases. The major challenges include complicated vessel structure, inhomogeneous illumination, and large background variation across subjects. In this study, we proposed an improved fully convolutional network that simultaneously segment arterioles and venules directly from the retinal image. To simultaneously segment retinal arterioles and venules, we configured the fully convolutional network to allow true color image as input and multiple labels as output. A domain-specific loss function is designed to improve the performance. The proposed method was assessed extensively on public datasets and compared with the state-of-the-art methods in literatures. The sensitivity and specificity of overall vessel segmentation on DRIVE is 0.870 and 0.980 with a misclassification rate of 23.7% and 9.8% for arteriole and venule, respectively. The proposed method outperforms the state-of-the-art methods and avoided possible error-propagation as in the segmentation-classification strategy. The proposed method holds great potential for the diagnostics and screening of various eye diseases and systemic diseases.

Originele taal-2Engels
TitelMedical Image Understanding and Analysis - 22nd Conference, Proceedings
RedacteurenMark Nixon, Sasan Mahmoodi, Reyer Zwiggelaar
Plaats van productieCham
UitgeverijSpringer
Pagina's333-340
Aantal pagina's8
ISBN van elektronische versie978-3-319-95921-4
ISBN van geprinte versie978-3-319-95920-7
DOI's
StatusGepubliceerd - 21 aug 2018
Evenement22nd Conference on Medical Image Understanding and Analysis (MIUA 2018) - University of Southampton, Southampton, Verenigd Koninkrijk
Duur: 9 jul 201811 jul 2018

Publicatie series

NaamCommunications in Computer and Information Science
Volume894
ISSN van geprinte versie1865-0929

Congres

Congres22nd Conference on Medical Image Understanding and Analysis (MIUA 2018)
Verkorte titelMIUA 2018
LandVerenigd Koninkrijk
StadSouthampton
Periode9/07/1811/07/18

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