{"id":"https://openalex.org/W7165612695","doi":"https://doi.org/10.48550/arxiv.2606.21756","title":"Scaling up fine-grained intracranial vessel annotations in computed tomography angiography","display_name":"Scaling up fine-grained intracranial vessel annotations in computed tomography angiography","publication_year":2026,"publication_date":"2026-06-19","ids":{"openalex":"https://openalex.org/W7165612695","doi":"https://doi.org/10.48550/arxiv.2606.21756"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.21756","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.21756","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.2606.21756","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038528790","display_name":"C Y Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Chu-Hsuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139215080","display_name":"Alberto Mario Ceballos-Arroyo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ceballos-Arroyo, Alberto Mario","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139201888","display_name":"Jisoo Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Jisoo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062744755","display_name":"Shrikanth Yadav","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yadav, Shrikanth M.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139128874","display_name":"Huaizu Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Huaizu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139210656","display_name":"Lei Qin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qin, Lei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5073315969","display_name":"Geoffrey S. Young","orcid":"https://orcid.org/0000-0001-8213-865X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Young, Geoffrey S.","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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.4560000002384186,"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"}},"topics":[{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.4560000002384186,"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"}},{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","score":0.12639999389648438,"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/T10816","display_name":"Cerebrovascular and Carotid Artery Diseases","score":0.09040000289678574,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.683899998664856},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.5515999794006348},{"id":"https://openalex.org/keywords/computed-tomography","display_name":"Computed tomography","score":0.541100025177002},{"id":"https://openalex.org/keywords/computed-tomography-angiography","display_name":"Computed tomography angiography","score":0.4803999960422516},{"id":"https://openalex.org/keywords/merge","display_name":"Merge (version control)","score":0.4375},{"id":"https://openalex.org/keywords/angiography","display_name":"Angiography","score":0.43230000138282776},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.32429999113082886}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.683899998664856},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5515999794006348},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5461000204086304},{"id":"https://openalex.org/C544519230","wikidata":"https://www.wikidata.org/wiki/Q32566","display_name":"Computed tomography","level":2,"score":0.541100025177002},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5304999947547913},{"id":"https://openalex.org/C2781347138","wikidata":"https://www.wikidata.org/wiki/Q1024492","display_name":"Computed tomography angiography","level":3,"score":0.4803999960422516},{"id":"https://openalex.org/C197129107","wikidata":"https://www.wikidata.org/wiki/Q1921621","display_name":"Merge (version control)","level":2,"score":0.4375},{"id":"https://openalex.org/C2780643987","wikidata":"https://www.wikidata.org/wiki/Q468414","display_name":"Angiography","level":2,"score":0.43230000138282776},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.38109999895095825},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.32429999113082886},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.31869998574256897},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3093000054359436},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3003999888896942},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.29820001125335693},{"id":"https://openalex.org/C2776820930","wikidata":"https://www.wikidata.org/wiki/Q9655","display_name":"Artery","level":2,"score":0.28850001096725464},{"id":"https://openalex.org/C171614378","wikidata":"https://www.wikidata.org/wiki/Q5064093","display_name":"Cerebral arteries","level":2,"score":0.2815999984741211},{"id":"https://openalex.org/C163716698","wikidata":"https://www.wikidata.org/wiki/Q841267","display_name":"Tomography","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.25360000133514404}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.21756","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.21756","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.2606.21756","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.21756","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"this":[1],"work,":[2],"we":[3,28,80],"present":[4],"SemanticVessel,":[5],"a":[6,86,100],"dataset":[7,119],"for":[8,32,99,106],"fine-grained":[9,139],"brain":[10],"vessel":[11],"segmentation":[12,30],"in":[13,51,109],"computed":[14],"tomography":[15],"angiography":[16],"scans.":[17],"Based":[18],"on":[19,167],"the":[20,46,52,92,110,115,132,142,156],"detailed":[21],"contrast":[22],"provided":[23],"by":[24,65],"dynamic":[25,96],"4D-CTA":[26],"scans,":[27],"generate":[29],"traces":[31],"arteries":[33,74,84],"and":[34,58,151,161],"veins.":[35],"We":[36,144],"then":[37],"use":[38],"intensity-guided":[39],"region":[40],"growing":[41],"to":[42,91,155],"obtain":[43],"segmentations":[44,140],"of":[45,48,95,117],"majority":[47],"vascular":[49],"territories":[50],"human":[53],"brain,":[54],"which":[55],"are":[56,75],"refined":[57],"annotated":[59],"with":[60,120,131],"20":[61],"unique":[62],"arterial":[63,88],"classes":[64],"an":[66],"expert":[67],"radiologist.":[68],"Unlike":[69],"existing":[70],"datasets,":[71],"where":[72],"minor":[73,83],"discarded":[76],"as":[77],"background":[78],"content,":[79],"merge":[81],"these":[82],"into":[85],"generic":[87,134],"class.":[89],"Due":[90],"multiple-phase":[93],"acquisition":[94],"4D-CTA,":[97],"labels":[98],"single":[101],"phase":[102],"can":[103],"be":[104,164],"re-used":[105],"other":[107],"phases":[108],"same":[111],"series,":[112],"greatly":[113],"increasing":[114],"size":[116],"our":[118,147],"no":[121],"additional":[122,133],"annotation":[123,149],"cost.":[124],"The":[125],"results":[126],"show":[127],"that":[128],"models":[129],"trained":[130],"artery":[135],"class":[136],"produce":[137],"better":[138],"across":[141],"board.":[143],"will":[145,163],"make":[146],"code,":[148],"GUI,":[150],"model":[152],"weights":[153],"available":[154,166],"scientific":[157],"community.":[158],"Code,":[159],"weights,":[160],"data":[162],"made":[165],"https://github.com/alceballosa/robust-vessel-segmentation":[168]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-24T00:00:00"}