{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T17:43:32Z","timestamp":1791395012260,"version":"4.3.3"},"reference-count":42,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T00:00:00Z","timestamp":1764633600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Pattern Recognition"],"published-print":{"date-parts":[[2026,5]]},"DOI":"10.1016\/j.patcog.2025.112797","type":"journal-article","created":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T00:31:20Z","timestamp":1764808280000},"page":"112797","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["Curvi-Tracker: Curvilinear structure segmentation refinement by iterative tracking"],"prefix":"10.1016","volume":"173","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-0658-9105","authenticated-orcid":false,"given":"Zhan","family":"Heng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7712-6646","authenticated-orcid":false,"given":"Maurice","family":"Pagnucco","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8015-8358","authenticated-orcid":false,"given":"Erik","family":"Meijering","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1283-1672","authenticated-orcid":false,"given":"Yang","family":"Song","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.patcog.2025.112797_bib0001","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.111254","article-title":"PA-Net: A hybrid architecture for retinal vessel segmentation","volume":"161","author":"Luo","year":"2025","journal-title":"Pattern Recognit."},{"issue":"7","key":"10.1016\/j.patcog.2025.112797_bib0002","doi-asserted-by":"crossref","first-page":"693","DOI":"10.1002\/cyto.a.20895","article-title":"Neuron tracing in perspective","volume":"77A","author":"Meijering","year":"2010","journal-title":"Cytometry Part A"},{"key":"10.1016\/j.patcog.2025.112797_bib0003","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2022.108549","article-title":"SDUNet: road extraction via spatial enhanced and densely connected UNet","volume":"126","author":"Yang","year":"2022","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2025.112797_bib0004","series-title":"Computer Vision: Statistical Models for Marr\u2019s Paradigm","first-page":"159","article-title":"Primal sketch: integrating textures and textons","author":"Zhu","year":"2023"},{"key":"10.1016\/j.patcog.2025.112797_bib0005","series-title":"Advances in Neural Information Processing Systems 2019","article-title":"Topology-preserving deep image segmentation","volume":"32","author":"Hu","year":"2019"},{"issue":"101874","key":"10.1016\/j.patcog.2025.112797_bib0006","article-title":"CS2-Net: curvilinear structure segmentation network for medical images","volume":"67","author":"Mou","year":"2020","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.patcog.2025.112797_bib0007","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.111302","article-title":"Edge-enhanced semi-supervised vertical convolutional neural network for tubular structure segmentation: application to medical images","volume":"162","author":"Zhao","year":"2025","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2025.112797_bib0008","series-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","first-page":"234","article-title":"U-Net: convolutional networks for biomedical image segmentation","volume":"9351","author":"Ronneberger","year":"2015"},{"key":"10.1016\/j.patcog.2025.112797_bib0009","series-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2016","first-page":"132","article-title":"DeepVessel: retinal vessel segmentation via deep learning and conditional random field","volume":"9901","author":"Fu","year":"2016"},{"key":"10.1016\/j.patcog.2025.112797_bib0010","series-title":"Computer Vision \u2013 ECCV 2022","first-page":"366","article-title":"PointScatter: point set representation for tubular structure extraction","volume":"13681","author":"Wang","year":"2022"},{"key":"10.1016\/j.patcog.2025.112797_bib0011","series-title":"2023 IEEE\/CVF International Conference on Computer Vision Workshops (ICCVW)","first-page":"2356","article-title":"Ensuring a connected structure for retinal vessels deep-learning segmentation","author":"Dulau","year":"2023"},{"key":"10.1016\/j.patcog.2025.112797_bib0012","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2023.110028","article-title":"Deep orientated distance-transform network for geometric-aware centerline detection","volume":"146","author":"Jiang","year":"2024","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2025.112797_bib0013","series-title":"2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"4720","article-title":"RoadTracer: automatic extraction of road networks from aerial images","author":"Bastani","year":"2018"},{"key":"10.1016\/j.patcog.2025.112797_bib0014","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.media.2018.10.005","article-title":"Coronary artery centerline extraction in cardiac CT angiography using a CNN-based orientation classifier","volume":"51","author":"Wolterink","year":"2019","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.patcog.2025.112797_bib0015","series-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2019","first-page":"468","article-title":"Discriminative coronary artery tracking via 3D CNN in cardiac CT angiography","volume":"11765","author":"Yang","year":"2019"},{"key":"10.1016\/j.patcog.2025.112797_bib0016","series-title":"2020 European Conference on Computer Vision (ECCV)","first-page":"213","article-title":"End-to-end object detection with transformers","volume":"12346","author":"Carion","year":"2020"},{"key":"10.1016\/j.patcog.2025.112797_bib0017","series-title":"2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"8907","article-title":"VecRoad: point-based iterative graph exploration for road graphs extraction","author":"Tan","year":"2020"},{"key":"10.1016\/j.patcog.2025.112797_bib0018","series-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2021","first-page":"418","article-title":"A deep reinforced tree-traversal agent for coronary artery centerline extraction","volume":"12905","author":"Li","year":"2021"},{"key":"10.1016\/j.patcog.2025.112797_bib0019","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2022.102724","article-title":"Deep reinforcement learning for cerebral anterior vessel tree extraction from 3D CTA images","volume":"84","author":"Su","year":"2023","journal-title":"Med. Image Anal."},{"issue":"5","key":"10.1016\/j.patcog.2025.112797_bib0020","doi-asserted-by":"crossref","first-page":"2991","DOI":"10.1109\/LRA.2023.3264723","article-title":"RNGDet++: road network graph detection by transformer with instance segmentation and multi-scale features enhancement","volume":"8","author":"Xu","year":"2023","journal-title":"IEEE Rob. Autom. Lett."},{"issue":"6","key":"10.1016\/j.patcog.2025.112797_bib0021","doi-asserted-by":"crossref","first-page":"1515","DOI":"10.1109\/TPAMI.2019.2921327","article-title":"Joint segmentation and path classification of curvilinear structures","volume":"42","author":"Mosinska","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.patcog.2025.112797_bib0022","series-title":"The 3rd International Conference on Learning Representations (ICLR2015)","first-page":"1","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2015"},{"key":"10.1016\/j.patcog.2025.112797_bib0023","series-title":"2023 IEEE\/CVF International Conference on Computer Vision (ICCV)","first-page":"6047","article-title":"Dynamic snake convolution based on topological geometric constraints for tubular structure segmentation","author":"Qi","year":"2023"},{"key":"10.1016\/j.patcog.2025.112797_bib0024","series-title":"2017 IEEE International Conference on Computer Vision (ICCV)","first-page":"764","article-title":"Deformable convolutional networks","author":"Dai","year":"2017"},{"key":"10.1016\/j.patcog.2025.112797_bib0025","series-title":"2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"16555","article-title":"clDice - a novel topology-Preserving loss function for tubular structure segmentation","author":"Shit","year":"2021"},{"key":"10.1016\/j.patcog.2025.112797_bib0026","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/j.neunet.2020.02.018","article-title":"NFN+: a novel network followed network for retinal vessel segmentation","volume":"126","author":"Wu","year":"2020","journal-title":"Neural Netw."},{"key":"10.1016\/j.patcog.2025.112797_bib0027","series-title":"2024 IEEE International Symposium on Biomedical Imaging (ISBI)","first-page":"1","article-title":"Vascular topology rectification network for automated retinal artery\/vein segmentation","author":"Heng","year":"2024"},{"key":"10.1016\/j.patcog.2025.112797_bib0028","series-title":"2017 IEEE International Conference on Computer Vision (ICCV)","first-page":"2410","article-title":"Multi-stage multi-recursive-input fully convolutional networks for neuronal boundary detection","author":"Shen","year":"2017"},{"key":"10.1016\/j.patcog.2025.112797_bib0029","series-title":"2019 IEEE\/CVF International Conference on Computer Vision (ICCV)","first-page":"2142","article-title":"Recurrent U-Net for resource-constrained segmentation","author":"Wang","year":"2019"},{"key":"10.1016\/j.patcog.2025.112797_bib0030","series-title":"2021 IEEE\/CVF International Conference on Computer Vision (ICCV)","first-page":"7127","article-title":"Joint topology-preserving and feature-refinement network for curvilinear structure segmentation","author":"Cheng","year":"2021"},{"key":"10.1016\/j.patcog.2025.112797_bib0031","series-title":"2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"12640","article-title":"Context-aware spatio-recurrent curvilinear structure segmentation","author":"Wang","year":"2019"},{"key":"10.1016\/j.patcog.2025.112797_bib0032","series-title":"2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"1800","article-title":"Xception: deep learning with depthwise separable convolutions","author":"Chollet","year":"2017"},{"issue":"2","key":"10.1016\/j.patcog.2025.112797_bib0033","doi-asserted-by":"crossref","first-page":"112","DOI":"10.3138\/FM57-6770-U75U-7727","article-title":"Algorithms for the reduction of the number of points required to represent a digitized line or its caricature","volume":"10","author":"Douglas","year":"1973","journal-title":"Cartographica: The International Journal for Geographic Information and Geovisualization"},{"key":"10.1016\/j.patcog.2025.112797_bib0034","series-title":"2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)","first-page":"1897","article-title":"Joint coronary centerline extraction and lumen segmentation from ccta using cnntracker and vascular graph convolutional network","author":"Gao","year":"2021"},{"issue":"4","key":"10.1016\/j.patcog.2025.112797_bib0035","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":"Staal","year":"2004","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.patcog.2025.112797_bib0036","series-title":"Machine Learning for Aerial Image Labeling","author":"Mnih","year":"2013"},{"issue":"3","key":"10.1016\/j.patcog.2025.112797_bib0037","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/j.patrec.2011.11.004","article-title":"CrackTree: automatic crack detection from pavement images","volume":"33","author":"Zou","year":"2012","journal-title":"Pattern Recognit. Lett."},{"key":"10.1016\/j.patcog.2025.112797_bib0038","first-page":"172","article-title":"Empirical evaluation of automatically extracted road axes","volume":"12","author":"Wiedemann","year":"1998","journal-title":"Empir. Eval. Tech. Comput. Vision"},{"key":"10.1016\/j.patcog.2025.112797_bib0039","series-title":"Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support","first-page":"3","article-title":"UNet++: a nested U-Net architecture for medical image segmentation","volume":"11045","author":"Zhou","year":"2018"},{"key":"10.1016\/j.patcog.2025.112797_bib0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.compmedimag.2022.102049","article-title":"Automated segmentation of normal and diseased coronary arteries \u2013 the ASOCA challenge","volume":"97","author":"Gharleghi","year":"2022","journal-title":"Comput. Med. Imaging Graphics"},{"key":"10.1016\/j.patcog.2025.112797_bib0041","doi-asserted-by":"crossref","DOI":"10.1016\/j.compmedimag.2023.102287","article-title":"ImageCAS: a large-scale dataset and benchmark for coronary artery segmentation based on computed tomography angiography images","volume":"109","author":"Zeng","year":"2023","journal-title":"Comput. Med. Imaging Graphics"},{"key":"10.1016\/j.patcog.2025.112797_bib0042","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.neunet.2023.01.031","article-title":"Fractional derivative based weighted skip connections for satellite image road segmentation","volume":"161","author":"Arora","year":"2023","journal-title":"Neural Netw."}],"container-title":["Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320325014608?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320325014608?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T21:06:26Z","timestamp":1772485586000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0031320325014608"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5]]},"references-count":42,"alternative-id":["S0031320325014608"],"URL":"https:\/\/doi.org\/10.1016\/j.patcog.2025.112797","relation":{},"ISSN":["0031-3203"],"issn-type":[{"value":"0031-3203","type":"print"}],"subject":[],"published":{"date-parts":[[2026,5]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Curvi-Tracker: Curvilinear structure segmentation refinement by iterative tracking","name":"articletitle","label":"Article Title"},{"value":"Pattern Recognition","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.patcog.2025.112797","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Author(s). Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"112797"}}