{"id":"https://openalex.org/W7125788711","doi":"https://doi.org/10.48550/arxiv.2601.17429","title":"Coronary Artery Segmentation and Vessel-Type Classification in X-Ray Angiography","display_name":"Coronary Artery Segmentation and Vessel-Type Classification in X-Ray Angiography","publication_year":2026,"publication_date":"2026-01-24","ids":{"openalex":"https://openalex.org/W7125788711","doi":"https://doi.org/10.48550/arxiv.2601.17429"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2601.17429","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.17429","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2601.17429","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5123938924","display_name":"Mehdi Yousefzadeh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yousefzadeh, Mehdi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123920562","display_name":"Siavash Shirzadeh Barough","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Barough, Siavash Shirzadeh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123921269","display_name":"Ashkan Fakharifar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fakharifar, Ashkan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123958834","display_name":"Yashar Tayyarazad","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tayyarazad, Yashar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123936237","display_name":"Narges Eghbali","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eghbali, Narges","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123931260","display_name":"Mohaddeseh Mozaffari","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mozaffari, Mohaddeseh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123916733","display_name":"Hoda Taeb","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Taeb, Hoda","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123934898","display_name":"Negar Sadat Rafiee Tabatabaee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tabatabaee, Negar Sadat Rafiee","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055416492","display_name":"Parsa Esfahanian","orcid":"https://orcid.org/0000-0001-6947-355X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Esfahanian, Parsa","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123883230","display_name":"Ghazaleh Sadeghi Gohar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gohar, Ghazaleh Sadeghi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124007818","display_name":"Amineh Safavirad","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Safavirad, Amineh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001179717","display_name":"Saeideh Mazloomzadeh","orcid":"https://orcid.org/0000-0001-6325-0662"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mazloomzadeh, Saeideh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088510648","display_name":"Ehsan Khalilipur","orcid":"https://orcid.org/0000-0001-5909-613X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"khalilipur, Ehsan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123947747","display_name":"Armin Elahifar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Elahifar, Armin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5123991911","display_name":"Majid Maleki","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Maleki, Majid","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10193","display_name":"Coronary Interventions and Diagnostics","score":0.3474000096321106,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10193","display_name":"Coronary Interventions and Diagnostics","score":0.3474000096321106,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","score":0.20730000734329224,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.1761000007390976,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6869000196456909},{"id":"https://openalex.org/keywords/dice","display_name":"Dice","score":0.6624000072479248},{"id":"https://openalex.org/keywords/s\u00f8rensen\u2013dice-coefficient","display_name":"S\u00f8rensen\u2013Dice coefficient","score":0.5874999761581421},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.542900025844574},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4593000113964081},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.39469999074935913},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.3831000030040741},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.3635999858379364}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7038999795913696},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6869000196456909},{"id":"https://openalex.org/C22029948","wikidata":"https://www.wikidata.org/wiki/Q45089","display_name":"Dice","level":2,"score":0.6624000072479248},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6183000206947327},{"id":"https://openalex.org/C163892561","wikidata":"https://www.wikidata.org/wiki/Q2613728","display_name":"S\u00f8rensen\u2013Dice coefficient","level":4,"score":0.5874999761581421},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.542900025844574},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4593000113964081},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.39469999074935913},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3831000030040741},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.3635999858379364},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3497999906539917},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.3375999927520752},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.33570000529289246},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.33379998803138733},{"id":"https://openalex.org/C203519979","wikidata":"https://www.wikidata.org/wiki/Q865360","display_name":"Jaccard index","level":3,"score":0.33340001106262207},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3328999876976013},{"id":"https://openalex.org/C2780643987","wikidata":"https://www.wikidata.org/wiki/Q468414","display_name":"Angiography","level":2,"score":0.30640000104904175},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.30059999227523804},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2851000130176544},{"id":"https://openalex.org/C3019004856","wikidata":"https://www.wikidata.org/wiki/Q42297149","display_name":"Coronary angiography","level":3,"score":0.25609999895095825},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.25589999556541443},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.2554999887943268},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2601.17429","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.17429","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2601.17429","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.17429","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"X-ray":[0],"coronary":[1,11,54],"angiography":[2],"(XCA)":[3],"is":[4,17],"the":[5,20,144],"clinical":[6],"reference":[7],"standard":[8],"for":[9,156,212,216,221],"assessing":[10],"artery":[12],"disease,":[13],"yet":[14],"quantitative":[15],"analysis":[16],"limited":[18],"by":[19],"difficulty":[21],"of":[22],"robust":[23],"vessel":[24,136],"segmentation":[25,38],"in":[26],"routine":[27],"data.":[28],"Low":[29],"contrast,":[30],"motion,":[31],"foreshortening,":[32],"overlap,":[33],"and":[34,39,56,83,87,94,107,121,128,173,193,203,218,233,238],"catheter":[35],"confounding":[36],"degrade":[37],"contribute":[40],"to":[41,179,190,201],"domain":[42],"shift":[43],"across":[44],"centers.":[45],"Reliable":[46],"segmentation,":[47],"together":[48],"with":[49,126,241],"vessel-type":[50],"labeling,":[51],"enables":[52],"vessel-specific":[53],"analytics":[55],"downstream":[57],"measurements":[58],"that":[59],"depend":[60],"on":[61],"anatomical":[62],"localization.":[63],"From":[64],"670":[65],"cine":[66],"sequences":[67],"(407":[68],"subjects),":[69],"we":[70],"select":[71],"a":[72,79,102,122,184],"best":[73],"frame":[74],"near":[75],"peak":[76],"opacification":[77],"using":[78],"low-intensity":[80],"histogram":[81],"criterion":[82],"apply":[84],"joint":[85],"super-resolution":[86],"enhancement.":[88],"We":[89],"benchmark":[90],"classical":[91,158,227],"Meijering,":[92],"Frangi,":[93],"Sato":[95],"vesselness":[96],"filters":[97,159],"under":[98],"per-image":[99,108,149,224],"oracle":[100],"tuning,":[101],"single":[103],"global":[104,154],"mean":[105],"setting,":[106],"parameter":[109],"prediction":[110],"via":[111],"Support":[112],"Vector":[113],"Regression":[114],"(SVR).":[115],"Neural":[116],"baselines":[117],"include":[118],"U-Net,":[119],"FPN,":[120],"Swin":[123],"Transformer,":[124],"trained":[125],"coronary-only":[127],"merged":[129,174],"coronary+catheter":[130,175],"supervision.":[131],"A":[132],"second":[133],"stage":[134],"assigns":[135],"identity":[137],"(LAD,":[138],"LCX,":[139],"RCA).":[140],"External":[141],"evaluation":[142],"uses":[143],"public":[145],"DCA1":[146,182],"cohort.":[147],"SVR":[148],"tuning":[150,225],"improves":[151],"Dice":[152,171,188],"over":[153],"means":[155],"all":[157],"(e.g.,":[160],"Frangi:":[161],"0.759":[162],"vs.":[163],"0.741).":[164],"Among":[165],"deep":[166],"models,":[167],"FPN":[168,231],"attains":[169],"0.914+/-0.007":[170],"(coronary-only),":[172],"labels":[176],"further":[177],"improve":[178,236],"0.931+/-0.006.":[180],"On":[181],"as":[183],"strict":[185],"external":[186,239],"test,":[187],"drops":[189],"0.798":[191],"(coronary-only)":[192],"0.814":[194],"(merged),":[195],"while":[196,229],"light":[197],"in-domain":[198],"fine-tuning":[199],"recovers":[200],"0.881+/-0.014":[202],"0.882+/-0.015.":[204],"Vessel-type":[205],"labeling":[206],"achieves":[207],"98.5%":[208],"accuracy":[209],"(Dice":[210],"0.844)":[211],"RCA,":[213],"95.4%":[214],"(0.786)":[215],"LAD,":[217],"96.2%":[219],"(0.794)":[220],"LCX.":[222],"Learned":[223],"strengthens":[226],"pipelines,":[228],"high-resolution":[230],"models":[232],"merged-label":[234],"supervision":[235],"stability":[237],"transfer":[240],"modest":[242],"adaptation.":[243]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-01-28T00:00:00"}
