{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T18:26:33Z","timestamp":1775067993947,"version":"3.50.1"},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2023,3,10]],"date-time":"2023-03-10T00:00:00Z","timestamp":1678406400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,3,10]],"date-time":"2023-03-10T00:00:00Z","timestamp":1678406400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100012245","name":"science and technology planning project of guangdong province","doi-asserted-by":"publisher","award":["180917144960530"],"award-info":[{"award-number":["180917144960530"]}],"id":[{"id":"10.13039\/501100012245","id-type":"DOI","asserted-by":"publisher"}]},{"name":"project of educational commission of guangdong province of china","award":["2017KZDXM032"],"award-info":[{"award-number":["2017KZDXM032"]}]},{"name":"science research startup foundation of shantou university","award":["NTF20021"],"award-info":[{"award-number":["NTF20021"]}]},{"DOI":"10.13039\/501100011133","name":"state key lab of digital manufacturing equipment and technology","doi-asserted-by":"publisher","award":["DMETKF2019020"],"award-info":[{"award-number":["DMETKF2019020"]}],"id":[{"id":"10.13039\/501100011133","id-type":"DOI","asserted-by":"publisher"}]},{"name":"robot automatic design platform combining multi-objective evolutionary computation and deep neural network","award":["2019A050519008"],"award-info":[{"award-number":["2019A050519008"]}]},{"DOI":"10.13039\/501100003453","name":"Guangdong Natural Science Foundation","doi-asserted-by":"crossref","award":["2022A1515011396"],"award-info":[{"award-number":["2022A1515011396"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["2021ZD0111502"],"award-info":[{"award-number":["2021ZD0111502"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Med Biol Eng Comput"],"published-print":{"date-parts":[[2023,7]]},"DOI":"10.1007\/s11517-023-02806-1","type":"journal-article","created":{"date-parts":[[2023,3,10]],"date-time":"2023-03-10T22:02:40Z","timestamp":1678485760000},"page":"1745-1755","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Segmentation of retinal vessels in fundus images based on U-Net with self-calibrated convolutions and spatial attention modules"],"prefix":"10.1007","volume":"61","author":[{"given":"YiBiao","family":"Rong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chong","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ying","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peiwei","family":"Wei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chuliang","family":"Wei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhun","family":"Fan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,3,10]]},"reference":[{"issue":"1","key":"2806_CR1","doi-asserted-by":"publisher","first-page":"014,006","DOI":"10.1117\/1.JMI.6.1.014006","volume":"6","author":"MZ Alom","year":"2019","unstructured":"Alom MZ, Yakopcic C, Hasan M, Taha TM, Asari VK (2019) Recurrent residual U-Net for medical image segmentation. J Med Imaging 6(1):014,006","journal-title":"J Med Imaging"},{"issue":"1","key":"2806_CR2","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.media.2014.08.002","volume":"19","author":"G Azzopardi","year":"2015","unstructured":"Azzopardi G, Strisciuglio N, Vento M, Petkov N (2015) Trainable cosfire filters for vessel delineation with application to retinal images. Med Image Anal 19(1):46\u201357","journal-title":"Med Image Anal"},{"issue":"5","key":"2806_CR3","doi-asserted-by":"publisher","first-page":"2367","DOI":"10.1109\/TIP.2018.2885495","volume":"28","author":"Z Fan","year":"2018","unstructured":"Fan Z, Lu J, Wei C, Huang H, Cai X, Chen X (2018) A hierarchical image matting model for blood vessel segmentation in fundus images. IEEE Trans Image Process 28(5):2367\u20132377","journal-title":"IEEE Trans Image Process"},{"issue":"9","key":"2806_CR4","doi-asserted-by":"publisher","first-page":"1515","DOI":"10.1007\/s11517-018-1793-4","volume":"56","author":"HR Fazlali","year":"2018","unstructured":"Fazlali HR, Karimi N, Soroushmehr SR, Shirani S, Nallamothu BK, Ward KR, Samavi S, Najarian K (2018) Vessel segmentation and catheter detection in x-ray angiograms using superpixels. Med Biol Eng Comput 56(9):1515\u20131530","journal-title":"Med Biol Eng Comput"},{"issue":"1","key":"2806_CR5","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1016\/j.cmpb.2012.03.009","volume":"108","author":"MM Fraz","year":"2012","unstructured":"Fraz MM, Remagnino P, Hoppe A, Uyyanonvara B, Rudnicka AR, Owen CG, Barman SA (2012) Blood vessel segmentation methodologies in retinal images\u2013a survey. Comput Methods Programs Biomed 108(1):407\u2013433","journal-title":"Comput Methods Programs Biomed"},{"issue":"9","key":"2806_CR6","doi-asserted-by":"publisher","first-page":"2538","DOI":"10.1109\/TBME.2012.2205687","volume":"59","author":"MM Fraz","year":"2012","unstructured":"Fraz MM, Remagnino P, Hoppe A, Uyyanonvara B, Rudnicka AR, Owen CG, Barman SA (2012) An ensemble classification-based approach applied to retinal blood vessel segmentation. IEEE Trans Biomed Eng 59(9):2538\u20132548","journal-title":"IEEE Trans Biomed Eng"},{"key":"2806_CR7","doi-asserted-by":"crossref","unstructured":"Guo C, Szemenyei M, Yi Y, Wang W, Chen B, Fan C (2020) SA-UNet: Spatial attention U-Net for retinal vessel segmentation. arXiv:2004.03696","DOI":"10.1007\/978-3-030-63830-6_43"},{"key":"2806_CR8","doi-asserted-by":"crossref","unstructured":"Guo X, Xiao R, Zhang T, Chen C, Wang J, Wang Z (2020) A novel method to model hepatic vascular network using vessel segmentation, thinning, and completion. Med Biol Eng Comput 1\u201316","DOI":"10.1007\/s11517-020-02128-6"},{"issue":"4","key":"2806_CR9","doi-asserted-by":"publisher","first-page":"395","DOI":"10.1016\/S0031-3203(97)00057-5","volume":"31","author":"Y Hamamoto","year":"1998","unstructured":"Hamamoto Y, Uchimura S, Watanabe M, Yasuda T, Mitani Y, Tomita S (1998) A Gabor filter-based method for recognizing handwritten numerals. Pattern Recogn 31(4):395\u2013400","journal-title":"Pattern Recogn"},{"issue":"7","key":"2806_CR10","doi-asserted-by":"publisher","first-page":"1369","DOI":"10.1109\/TMI.2010.2043259","volume":"29","author":"BS Lam","year":"2010","unstructured":"Lam BS, Gao Y, Liew AWC (2010) General retinal vessel segmentation using regularization-based multiconcavity modeling. IEEE Trans Med Imaging 29(7):1369\u20131381","journal-title":"IEEE Trans Med Imaging"},{"issue":"7553","key":"2806_CR11","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y Lecun","year":"2015","unstructured":"Lecun Y, Bengio Y, Hinton GE (2015) Deep learning. Nature 521(7553):436\u2013444","journal-title":"Nature"},{"issue":"11","key":"2806_CR12","doi-asserted-by":"publisher","first-page":"2278","DOI":"10.1109\/5.726791","volume":"86","author":"Y Lecun","year":"1998","unstructured":"Lecun Y, Bottou L, Bengio Y, Haffner P (1998) Gradient-based learning applied to document recognition. Proc IEEE 86(11):2278\u20132324","journal-title":"Proc IEEE"},{"issue":"1","key":"2806_CR13","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1109\/TMI.2015.2457891","volume":"35","author":"Q Li","year":"2015","unstructured":"Li Q, Feng B, Xie L, Liang P, Zhang H, Wang T (2015) A cross-modality learning approach for vessel segmentation in retinal images. IEEE Trans Med Imaging 35(1):109\u2013118","journal-title":"IEEE Trans Med Imaging"},{"issue":"5","key":"2806_CR14","doi-asserted-by":"publisher","first-page":"785","DOI":"10.1016\/j.engappai.2007.07.001","volume":"21","author":"X Li","year":"2008","unstructured":"Li X, Wang L, Sung E (2008) AdaBoost with SVM-based component classifiers. Eng Appl Artif Intel 21(5):785\u2013795","journal-title":"Eng Appl Artif Intel"},{"issue":"11","key":"2806_CR15","doi-asserted-by":"publisher","first-page":"2369","DOI":"10.1109\/TMI.2016.2546227","volume":"35","author":"P Liskowski","year":"2016","unstructured":"Liskowski P, Krawiec K (2016) Segmenting retinal blood vessels with deep neural networks. IEEE Trans Med Imaging 35(11):2369\u20132380","journal-title":"IEEE Trans Med Imaging"},{"issue":"2","key":"2806_CR16","doi-asserted-by":"publisher","first-page":"334","DOI":"10.1109\/42.232264","volume":"12","author":"I Liu","year":"1993","unstructured":"Liu I, Sun Y (1993) Recursive tracking of vascular networks in angiograms based on the detection-deletion scheme. IEEE Trans Med Imaging 12(2):334\u2013341","journal-title":"IEEE Trans Med Imaging"},{"key":"2806_CR17","doi-asserted-by":"crossref","unstructured":"Liu JJ, Hou Q, Cheng MM, Wang C, Feng J (2020) Improving convolutional networks with self-calibrated convolutions. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 10,096\u201310,105","DOI":"10.1109\/CVPR42600.2020.01011"},{"issue":"9","key":"2806_CR18","doi-asserted-by":"publisher","first-page":"1200","DOI":"10.1109\/TMI.2006.879955","volume":"25","author":"AM Mendonca","year":"2006","unstructured":"Mendonca AM, Campilho A (2006) Segmentation of retinal blood vessels by combining the detection of centerlines and morphological reconstruction. IEEE Trans Med Imaging 25(9):1200\u20131213","journal-title":"IEEE Trans Med Imaging"},{"key":"2806_CR19","doi-asserted-by":"publisher","first-page":"101,874","DOI":"10.1016\/j.media.2020.101874","volume":"67","author":"L Mou","year":"2021","unstructured":"Mou L, Zhao Y, Fu H, Liu Y, Cheng J, Zheng Y, Su P, Yang J, Chen L, Frangi AF et al (2021) CS2-Net: Deep learning segmentation of curvilinear structures in medical imaging. Med Image Anal 67:101,874","journal-title":"Med Image Anal"},{"key":"2806_CR20","doi-asserted-by":"crossref","unstructured":"Nguyen V, Blumenstein M (2011) An application of the 2D gaussian filter for enhancing feature extraction in off-line signature verification. In: 2011 international conference on document analysis and recognition. IEEE, pp 339\u2013343","DOI":"10.1109\/ICDAR.2011.76"},{"issue":"10","key":"2806_CR21","doi-asserted-by":"publisher","first-page":"1357","DOI":"10.1109\/TMI.2007.898551","volume":"26","author":"E Ricci","year":"2007","unstructured":"Ricci E, Perfetti R (2007) Retinal blood vessel segmentation using line operators and support vector classification. IEEE Trans Med Imaging 26(10):1357\u20131365","journal-title":"IEEE Trans Med Imaging"},{"key":"2806_CR22","doi-asserted-by":"crossref","unstructured":"Ronneberger O, Fischer P, Brox T (2015) U-Net: Convolutional networks for biomedical image segmentation. In: International Conference on Medical image computing and computer-assisted intervention. Springer, pp 234\u2013241","DOI":"10.1007\/978-3-319-24574-4_28"},{"issue":"3","key":"2806_CR23","first-page":"1118","volume":"19","author":"S Roychowdhury","year":"2014","unstructured":"Roychowdhury S, Koozekanani DD, Parhi KK (2014) Blood vessel segmentation of fundus images by major vessel extraction and subimage classification. IEEE J Biomed Health Inf 19(3):1118\u20131128","journal-title":"IEEE J Biomed Health Inf"},{"issue":"3","key":"2806_CR24","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1007\/s11517-006-0141-2","volume":"45","author":"SA Salem","year":"2007","unstructured":"Salem SA, Salem NM, Nandi AK (2007) Segmentation of retinal blood vessels using a novel clustering algorithm (RACAL) with a partial supervision strategy. Med Biol Eng Comput 45(3):261\u2013273","journal-title":"Med Biol Eng Comput"},{"issue":"4","key":"2806_CR25","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1109\/TMI.2004.825627","volume":"23","author":"J Staal","year":"2004","unstructured":"Staal J, Abr\u00e0moff MD, Niemeijer M, Viergever MA, Van Ginneken B (2004) Ridge-based vessel segmentation in color images of the retina. IEEE Trans Med Imaging 23(4):501\u2013509","journal-title":"IEEE Trans Med Imaging"},{"key":"2806_CR26","doi-asserted-by":"crossref","unstructured":"Wang B, Qiu S, He H (2019) Dual encoding U-Net for retinal vessel segmentation. In: International conference on medical image computing and computer-assisted intervention. Springer, pp 84\u201392","DOI":"10.1007\/978-3-030-32239-7_10"},{"issue":"4","key":"2806_CR27","doi-asserted-by":"publisher","first-page":"1128","DOI":"10.1109\/JBHI.2020.3011178","volume":"25","author":"B Wang","year":"2020","unstructured":"Wang B, Wang S, Qiu S, Wei W, Wang H, He H (2020) CSU-Net: a context spatial u-net for accurate blood vessel segmentation in fundus images. IEEE J Biomed Health Inform 25(4):1128\u20131138","journal-title":"IEEE J Biomed Health Inform"},{"issue":"7","key":"2806_CR28","doi-asserted-by":"publisher","first-page":"1481","DOI":"10.1007\/s11517-019-01967-2","volume":"57","author":"W Wang","year":"2019","unstructured":"Wang W, Wang W, Hu Z (2019) Segmenting retinal vessels with revised top-bottom-hat transformation and flattening of minimum circumscribed ellipse. Med Biol Eng Comput 57(7):1481\u20131496","journal-title":"Med Biol Eng Comput"},{"issue":"2","key":"2806_CR29","doi-asserted-by":"publisher","first-page":"292","DOI":"10.1109\/TMI.2021.3111679","volume":"41","author":"J Wei","year":"2022","unstructured":"Wei J, Zhu G, Fan Z, Liu J, Rong Y, Mo J, Li W, Chen X (2022) Genetic U-Net: automatically designed deep networks for retinal vessel segmentation using a genetic algorithm. IEEE Trans Med Imaging 41(2):292\u2013307","journal-title":"IEEE Trans Med Imaging"},{"key":"2806_CR30","doi-asserted-by":"crossref","unstructured":"Woo S, Park J, Lee JY, Kweon IS (2018) CBAM: Convolutional block attention module. In: Proceedings of the European conference on computer vision (ECCV), pp 3\u201319","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"2806_CR31","doi-asserted-by":"crossref","unstructured":"Wu Y, Xia Y, Song Y, Zhang Y, Cai W (2018) Multiscale network followed network model for retinal vessel segmentation. In: International conference on medical image computing and computer-assisted intervention. Springer, pp 119\u2013126","DOI":"10.1007\/978-3-030-00934-2_14"},{"issue":"9","key":"2806_CR32","doi-asserted-by":"publisher","first-page":"1797","DOI":"10.1109\/TMI.2015.2409024","volume":"34","author":"Y Zhao","year":"2015","unstructured":"Zhao Y, Rada L, Chen K, Harding SP, Zheng Y (2015) Automated vessel segmentation using infinite perimeter active contour model with hybrid region information with application to retinal images. IEEE Trans Med Imaging 34(9):1797\u20131807","journal-title":"IEEE Trans Med Imaging"}],"container-title":["Medical &amp; Biological Engineering &amp; Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-023-02806-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11517-023-02806-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-023-02806-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,19]],"date-time":"2023-06-19T01:04:53Z","timestamp":1687136693000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11517-023-02806-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,10]]},"references-count":32,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2023,7]]}},"alternative-id":["2806"],"URL":"https:\/\/doi.org\/10.1007\/s11517-023-02806-1","relation":{},"ISSN":["0140-0118","1741-0444"],"issn-type":[{"value":"0140-0118","type":"print"},{"value":"1741-0444","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,10]]},"assertion":[{"value":"5 July 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 February 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 March 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Competing interests"}}]}}