{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T19:06:20Z","timestamp":1771959980785,"version":"3.50.1"},"reference-count":29,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T00:00:00Z","timestamp":1585699200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T00:00:00Z","timestamp":1585699200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"}],"funder":[{"DOI":"10.13039\/501100010801","name":"Xunta de Galicia","doi-asserted-by":"publisher","award":["ED431C 2016-047"],"award-info":[{"award-number":["ED431C 2016-047"]}],"id":[{"id":"10.13039\/501100010801","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010801","name":"Xunta de Galicia","doi-asserted-by":"publisher","award":["ED431G\/01"],"award-info":[{"award-number":["ED431G\/01"]}],"id":[{"id":"10.13039\/501100010801","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010801","name":"Xunta de Galicia","doi-asserted-by":"publisher","award":["ED481A-2017\/328"],"award-info":[{"award-number":["ED481A-2017\/328"]}],"id":[{"id":"10.13039\/501100010801","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100014440","name":"Ministerio de Ciencia, Innovaci\u00f3n y Universidades","doi-asserted-by":"publisher","award":["DPI2015-69948-R"],"award-info":[{"award-number":["DPI2015-69948-R"]}],"id":[{"id":"10.13039\/100014440","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100014440","name":"Ministerio de Ciencia, Innovaci\u00f3n y Universidades","doi-asserted-by":"publisher","award":["RTI2018-095894-B-I00"],"award-info":[{"award-number":["RTI2018-095894-B-I00"]}],"id":[{"id":"10.13039\/100014440","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018942","name":"Centro Singular de Investigaci\u00f3n de Galicia","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100018942","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000780","name":"European Commission","doi-asserted-by":"publisher","award":["DTS18\/00136"],"award-info":[{"award-number":["DTS18\/00136"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004587","name":"Instituto de Salud Carlos III","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004587","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004895","name":"European Social Fund","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004895","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computer Methods and Programs in Biomedicine"],"published-print":{"date-parts":[[2020,4]]},"DOI":"10.1016\/j.cmpb.2019.105201","type":"journal-article","created":{"date-parts":[[2019,11,12]],"date-time":"2019-11-12T02:30:56Z","timestamp":1573525856000},"page":"105201","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":37,"special_numbering":"C","title":["Deep multi-instance heatmap regression for the detection of retinal vessel crossings and bifurcations in eye fundus images"],"prefix":"10.1016","volume":"186","author":[{"given":"\u00c1lvaro S.","family":"Hervella","sequence":"first","affiliation":[]},{"given":"Jos\u00e9","family":"Rouco","sequence":"additional","affiliation":[]},{"given":"Jorge","family":"Novo","sequence":"additional","affiliation":[]},{"given":"Manuel G.","family":"Penedo","sequence":"additional","affiliation":[]},{"given":"Marcos","family":"Ortega","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.cmpb.2019.105201_bib0001","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.preteyeres.2005.07.001","article-title":"Retinal image analysis: concepts, applications and potential","volume":"25","author":"Patton","year":"2006","journal-title":"Prog. Retin. Eye Res."},{"key":"10.1016\/j.cmpb.2019.105201_bib0002","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1109\/RBME.2010.2084567","article-title":"Retinal imaging and image analysis","volume":"3","author":"Abramoff","year":"2010","journal-title":"IEEE Rev. Biomed. Eng."},{"issue":"1","key":"10.1016\/j.cmpb.2019.105201_bib0003","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/S0039-6257(01)00234-X","article-title":"Retinal microvascular abnormalities and their relationship with hypertension, cardiovascular disease, and mortality","volume":"46","author":"Wong","year":"2001","journal-title":"Surv. Ophthalmol."},{"key":"10.1016\/j.cmpb.2019.105201_sbref0004","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/j.cmpb.2017.11.014","article-title":"Arteriovenous ratio and papilledema based hybrid decision support system for detection and grading of hypertensive retinopathy","volume":"154","author":"Akbar","year":"2018","journal-title":"Comput. Methods Programs Biomed."},{"issue":"3","key":"10.1016\/j.cmpb.2019.105201_bib0005","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1109\/TMI.2007.904657","article-title":"A novel method for the automatic grading of retinal vessel tortuosity","volume":"27","author":"Grisan","year":"2008","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.cmpb.2019.105201_bib0006","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.cmpb.2017.08.018","article-title":"Vascular tree tracking and bifurcation points detection in retinal images using a hierarchical probabilistic model","volume":"151","author":"Kalaie","year":"2017","journal-title":"Comput. Methods Programs Biomed."},{"key":"10.1016\/j.cmpb.2019.105201_bib0007","series-title":"International Conference on Knowledge-Based and Intelligent Information and Engineering Systems (KES)","article-title":"Multimodal registration of retinal images using domain-specific landmarks and vessel enhancement","author":"Hervella","year":"2018"},{"issue":"1","key":"10.1016\/j.cmpb.2019.105201_bib0008","doi-asserted-by":"crossref","first-page":"235746","DOI":"10.1155\/2009\/235746","article-title":"Retinal verification using a feature points-based biometric pattern","volume":"2009","author":"Ortega","year":"2009","journal-title":"EURASIP J. Adv. Signal Process."},{"key":"10.1016\/j.cmpb.2019.105201_bib0009","series-title":"Medical Image Computing and Computer-Assisted Intervention (MICCAI)","article-title":"Deep Retinal Image Understanding","author":"Maninis","year":"2016"},{"key":"10.1016\/j.cmpb.2019.105201_sbref0010","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.cmpb.2018.02.016","article-title":"Microaneurysm detection using fully convolutional neural networks","volume":"158","author":"Chudzik","year":"2018","journal-title":"Comput. Methods Programs Biomed."},{"key":"10.1016\/j.cmpb.2019.105201_bib0011","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.media.2017.07.005","article-title":"A survey on deep learning in medical image analysis","volume":"42","author":"Litjens","year":"2017","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.cmpb.2019.105201_bib0012","series-title":"2016\u202fIEEE 13th International Symposium on Biomedical Imaging (ISBI)","first-page":"189","article-title":"Automatic detection of vascular bifurcations and crossings in retinal images using orientation scores","author":"Abbasi-Sureshjani","year":"2016"},{"issue":"1","key":"10.1016\/j.cmpb.2019.105201_sbref0013","doi-asserted-by":"crossref","DOI":"10.3390\/jimaging4010004","article-title":"Automatic detection and distinction of retinal vessel bifurcations and crossings in colour fundus photography","volume":"4","author":"Pratt","year":"2018","journal-title":"J. Imaging"},{"key":"10.1016\/j.cmpb.2019.105201_bib0014","series-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2018","first-page":"92","article-title":"A multi-task network to detect junctions in retinal vasculature","author":"Uslu","year":"2018"},{"issue":"8","key":"10.1016\/j.cmpb.2019.105201_sbref0015","doi-asserted-by":"crossref","first-page":"922","DOI":"10.1016\/j.patrec.2012.11.002","article-title":"Automatic detection of vascular bifurcations in segmented retinal images using trainable COSFIRE filters","volume":"34","author":"Azzopardi","year":"2013","journal-title":"Pattern Recognit. Lett."},{"issue":"1","key":"10.1016\/j.cmpb.2019.105201_sbref0016","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.cmpb.2010.06.002","article-title":"Automatic detection and characterisation of retinal vessel tree bifurcations and crossovers in eye fundus images","volume":"103","author":"Calvo","year":"2011","journal-title":"Comput. Methods Programs Biomed."},{"issue":"1","key":"10.1016\/j.cmpb.2019.105201_sbref0017","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.compbiomed.2009.11.004","article-title":"Vascular intersection detection in retina fundus images using a new hybrid approach","volume":"40","author":"Aibinu","year":"2010","journal-title":"Comput. Biol. Med."},{"issue":"5","key":"10.1016\/j.cmpb.2019.105201_sbref0018","doi-asserted-by":"crossref","first-page":"587","DOI":"10.1016\/j.compbiomed.2013.01.011","article-title":"Automatic vessel network features quantification using local vessel pattern operator","volume":"43","author":"Fathi","year":"2013","journal-title":"Comput. Biol. Med."},{"issue":"3","key":"10.1016\/j.cmpb.2019.105201_sbref0019","doi-asserted-by":"crossref","first-page":"189","DOI":"10.5566\/ias.1101","article-title":"Automatic detection and classification of retinal vascular landmarks","volume":"33","author":"Hamad","year":"2014","journal-title":"Image Anal. Stereol."},{"issue":"2","key":"10.1016\/j.cmpb.2019.105201_bib0020","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1109\/TITB.2004.826733","article-title":"Model-based method for improving the accuracy and repeatability of estimating vascular bifurcations and crossovers from retinal fundus images","volume":"8","author":"Tsai","year":"2004","journal-title":"IEEE Trans. Inf. Technol. Biomed."},{"key":"10.1016\/j.cmpb.2019.105201_bib0021","series-title":"International Conference on Computer Vision","article-title":"Flowing convnets for human pose estimation in videos","author":"Pfister","year":"2015"},{"key":"10.1016\/j.cmpb.2019.105201_bib0022","series-title":"The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","article-title":"Robust facial landmark detection via a fully-convolutional local-global context network","author":"Merget","year":"2018"},{"key":"10.1016\/j.cmpb.2019.105201_bib0023","series-title":"Medical Image Computing and Computer-Assisted Intervention (MICCAI)","article-title":"U-Net: convolutional networks for biomedical image segmentation","author":"Ronneberger","year":"2015"},{"key":"10.1016\/j.cmpb.2019.105201_bib0024","series-title":"Medical Image Computing and Computer-Assisted Intervention (MICCAI)","article-title":"Retinal image understanding emerges from self-supervised multimodal reconstruction","author":"Hervella","year":"2018"},{"key":"10.1016\/j.cmpb.2019.105201_bib0025","series-title":"International Joint Conference on Neural Networks (IJCNN)","article-title":"Self-supervised deep learning for retinal vessel segmentation using automatically generated labels from multimodal data","author":"Hervella","year":"2019"},{"key":"10.1016\/j.cmpb.2019.105201_bib0026","series-title":"International Conference on Computer Vision (ICCV)","article-title":"Delving deep into rectifiers: surpassing human-level performance on imagenet classification","author":"He","year":"2015"},{"key":"10.1016\/j.cmpb.2019.105201_bib0027","series-title":"International Conference on Learning Representations (ICLR)","article-title":"Adam: a method for stochastic optimization","author":"Kingma","year":"2015"},{"issue":"11","key":"10.1016\/j.cmpb.2019.105201_bib0028","doi-asserted-by":"crossref","first-page":"2369","DOI":"10.1109\/TMI.2016.2546227","article-title":"Segmenting retinal blood vessels with deep neural networks","volume":"35","author":"Liskowski","year":"2016","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"4","key":"10.1016\/j.cmpb.2019.105201_bib0029","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1109\/TMI.2004.825627","article-title":"Ridge based vessel segmentation in color images of the retina","volume":"23","author":"van Ginneken","year":"2004","journal-title":"IEEE Trans. Med. Imaging"}],"container-title":["Computer Methods and Programs in Biomedicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0169260719307837?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0169260719307837?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T03:52:21Z","timestamp":1759204341000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0169260719307837"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4]]},"references-count":29,"alternative-id":["S0169260719307837"],"URL":"https:\/\/doi.org\/10.1016\/j.cmpb.2019.105201","relation":{},"ISSN":["0169-2607"],"issn-type":[{"value":"0169-2607","type":"print"}],"subject":[],"published":{"date-parts":[[2020,4]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Deep multi-instance heatmap regression for the detection of retinal vessel crossings and bifurcations in eye fundus images","name":"articletitle","label":"Article Title"},{"value":"Computer Methods and Programs in Biomedicine","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cmpb.2019.105201","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2019 Elsevier B.V. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"105201"}}