{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T18:13:17Z","timestamp":1773943997972,"version":"3.50.1"},"reference-count":47,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2021,9,29]],"date-time":"2021-09-29T00:00:00Z","timestamp":1632873600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61962054"],"award-info":[{"award-number":["61962054"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61163036"],"award-info":[{"award-number":["61163036"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"2016 Gansu Provincial Science and Technology Plan Funded by the Natural Science Foundation 356 of China","award":["1606RJZA047"],"award-info":[{"award-number":["1606RJZA047"]}]},{"name":"Northwest Normal University Major Research Project 359 Incubation Program","award":["NWNU-LKZD2021_06"],"award-info":[{"award-number":["NWNU-LKZD2021_06"]}]},{"name":"Northwest Normal University\u2019s Third Phase of Knowledge and Innovation Engineering Research Backbone Project","award":["nwnu-kjcxgc-03-67"],"award-info":[{"award-number":["nwnu-kjcxgc-03-67"]}]},{"name":"2012 Gansu Provincial University Fundamental Research Fund for Special Research Funds, Gansu Province Postgraduate Supervisor Program in Colleges and Universities","award":["1201-16"],"award-info":[{"award-number":["1201-16"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>The segmentation of retinal vessels is critical for the diagnosis of some fundus diseases. Retinal vessel segmentation requires abundant spatial information and receptive fields with different sizes while existing methods usually sacrifice spatial resolution to achieve real-time reasoning speed, resulting in inadequate vessel segmentation of low-contrast regions and weak anti-noise interference ability. The asymmetry of capillaries in fundus images also increases the difficulty of segmentation. In this paper, we proposed a two-branch network based on multi-scale attention to alleviate the above problem. First, a coarse network with multi-scale U-Net as the backbone is designed to capture more semantic information and to generate high-resolution features. A multi-scale attention module is used to obtain enough receptive fields. The other branch is a fine network, which uses the residual block of a small convolution kernel to make up for the deficiency of spatial information. Finally, we use the feature fusion module to aggregate the information of the coarse and fine networks. The experiments were performed on the DRIVE, CHASE, and STARE datasets. Respectively, the accuracy reached 96.93%, 97.58%, and 97.70%. The specificity reached 97.72%, 98.52%, and 98.94%. The F-measure reached 83.82%, 81.39%, and 84.36%. Experimental results show that compared with some state-of-art methods such as Sine-Net, SA-Net, our proposed method has better performance on three datasets.<\/jats:p>","DOI":"10.3390\/sym13101820","type":"journal-article","created":{"date-parts":[[2021,10,11]],"date-time":"2021-10-11T01:59:47Z","timestamp":1633917587000},"page":"1820","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Bi-SANet\u2014Bilateral Network with Scale Attention for Retinal Vessel Segmentation"],"prefix":"10.3390","volume":"13","author":[{"given":"Yun","family":"Jiang","sequence":"first","affiliation":[{"name":"College of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3184-9897","authenticated-orcid":false,"given":"Huixia","family":"Yao","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zeqi","family":"Ma","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingyao","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1001\/jamaophthalmol.2013.1743","article-title":"Automated analysis of retinal images for detection of referable diabetic retinopathy","volume":"131","author":"Folk","year":"2013","journal-title":"JAMA Ophthalmol."},{"key":"ref_2","first-page":"175","article-title":"Prevalence of Asymptomatic Eye Disease Pr\u00e9valence des maladies oculaires asymptomatiques","volume":"65","author":"Robinson","year":"2003","journal-title":"Rev. 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