{"id":"https://openalex.org/W4401114144","doi":"https://doi.org/10.1109/tmi.2024.3435714","title":"Segmentation and Vascular Vectorization for Coronary Artery by Geometry-Based Cascaded Neural Network","display_name":"Segmentation and Vascular Vectorization for Coronary Artery by Geometry-Based Cascaded Neural Network","publication_year":2024,"publication_date":"2024-07-30","ids":{"openalex":"https://openalex.org/W4401114144","doi":"https://doi.org/10.1109/tmi.2024.3435714","pmid":"https://pubmed.ncbi.nlm.nih.gov/39078771"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2024.3435714","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2024.3435714","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050375803","display_name":"Xiaoyu Yang","orcid":"https://orcid.org/0000-0003-0273-9573"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4391012619","display_name":"Shanghai Artificial Intelligence Laboratory","ror":"https://ror.org/03wkvpx79","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4391012619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyu Yang","raw_affiliation_strings":["Shanghai Artificial Intelligence Laboratory, Shanghai, China","College of Electronics and Information Engineering, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-0273-9573","affiliations":[{"raw_affiliation_string":"Shanghai Artificial Intelligence Laboratory, Shanghai, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4391012619"]},{"raw_affiliation_string":"College of Electronics and Information Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090398317","display_name":"Lijian Xu","orcid":"https://orcid.org/0000-0002-6632-4011"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4391012619","display_name":"Shanghai Artificial Intelligence Laboratory","ror":"https://ror.org/03wkvpx79","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4391012619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lijian Xu","raw_affiliation_strings":["Shanghai Artificial Intelligence Laboratory, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-6632-4011","affiliations":[{"raw_affiliation_string":"Shanghai Artificial Intelligence Laboratory, Shanghai, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4391012619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040190424","display_name":"Simon C.H. Yu","orcid":"https://orcid.org/0000-0002-8715-5026"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Simon Yu","raw_affiliation_strings":["Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, Hong Kong","Department of Imaging and Interventional Radiology, Chinese University of Hong Kong, Hongkong, China"],"raw_orcid":"https://orcid.org/0000-0002-8715-5026","affiliations":[{"raw_affiliation_string":"Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, Hong Kong","institution_ids":["https://openalex.org/I177725633"]},{"raw_affiliation_string":"Department of Imaging and Interventional Radiology, Chinese University of Hong Kong, Hongkong, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102011770","display_name":"Qing Xia","orcid":"https://orcid.org/0000-0002-0328-7882"},"institutions":[{"id":"https://openalex.org/I4210128910","display_name":"Group Sense (China)","ror":"https://ror.org/036wd5777","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Xia","raw_affiliation_strings":["SenseTime Research, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-0328-7882","affiliations":[{"raw_affiliation_string":"SenseTime Research, Shanghai, China","institution_ids":["https://openalex.org/I4210128910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100732450","display_name":"Hongsheng Li","orcid":"https://orcid.org/0000-0002-2664-7975"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]},{"id":"https://openalex.org/I4210159835","display_name":"Perceptive Engineering (United Kingdom)","ror":"https://ror.org/05qep9y26","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210159835"]}],"countries":["GB","HK"],"is_corresponding":false,"raw_author_name":"Hongsheng Li","raw_affiliation_strings":["Centre for Perceptual and Interactive Intelligence, Pak Shek Kok, Hong Kong","Department of Electronic Engineering, Chinese University of Hong Kong, Hongkong, China"],"raw_orcid":"https://orcid.org/0000-0002-2664-7975","affiliations":[{"raw_affiliation_string":"Centre for Perceptual and Interactive Intelligence, Pak Shek Kok, Hong Kong","institution_ids":["https://openalex.org/I4210159835"]},{"raw_affiliation_string":"Department of Electronic Engineering, Chinese University of Hong Kong, Hongkong, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103125173","display_name":"Shaoting Zhang","orcid":"https://orcid.org/0000-0002-0057-2944"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4391012619","display_name":"Shanghai Artificial Intelligence Laboratory","ror":"https://ror.org/03wkvpx79","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4391012619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaoting Zhang","raw_affiliation_strings":["Shanghai Artificial Intelligence Laboratory, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Artificial Intelligence Laboratory, Shanghai, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4391012619"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.6846,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.97623787,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"44","issue":"1","first_page":"259","last_page":"269"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10193","display_name":"Coronary Interventions and Diagnostics","score":0.7498000264167786,"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":0.7498000264167786,"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/T12979","display_name":"Cardiovascular Disease and Adiposity","score":0.6898000240325928,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/T10924","display_name":"Cardiovascular Health and Disease Prevention","score":0.6729999780654907,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular 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/vectorization","display_name":"Vectorization (mathematics)","score":0.7682465314865112},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5598214864730835},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5356838703155518},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5322093367576599},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5250770449638367},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4877508282661438},{"id":"https://openalex.org/keywords/artery","display_name":"Artery","score":0.44711464643478394},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.420634925365448},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.3556761145591736},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.28080642223358154},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.24209800362586975},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24127545952796936}],"concepts":[{"id":"https://openalex.org/C41681595","wikidata":"https://www.wikidata.org/wiki/Q7917855","display_name":"Vectorization (mathematics)","level":2,"score":0.7682465314865112},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5598214864730835},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5356838703155518},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5322093367576599},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5250770449638367},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4877508282661438},{"id":"https://openalex.org/C2776820930","wikidata":"https://www.wikidata.org/wiki/Q9655","display_name":"Artery","level":2,"score":0.44711464643478394},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.420634925365448},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.3556761145591736},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.28080642223358154},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.24209800362586975},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24127545952796936},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000072226","descriptor_name":"Computed Tomography Angiography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D000072226","descriptor_name":"Computed Tomography Angiography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D000072226","descriptor_name":"Computed Tomography Angiography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D000072226","descriptor_name":"Computed Tomography Angiography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003331","descriptor_name":"Coronary Vessels","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D003331","descriptor_name":"Coronary Vessels","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D003331","descriptor_name":"Coronary Vessels","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D003331","descriptor_name":"Coronary Vessels","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D017023","descriptor_name":"Coronary Angiography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D017023","descriptor_name":"Coronary Angiography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D017023","descriptor_name":"Coronary Angiography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D017023","descriptor_name":"Coronary Angiography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/tmi.2024.3435714","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2024.3435714","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},{"id":"pmid:39078771","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39078771","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on medical imaging","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2842882394","display_name":null,"funder_award_id":"Z201100006820064, Z211100002121165","funder_id":"https://openalex.org/F4320334978","funder_display_name":"Beijing Nova Program"},{"id":"https://openalex.org/G3972538984","display_name":null,"funder_award_id":"Z211100002121165","funder_id":"https://openalex.org/F4320334978","funder_display_name":"Beijing Nova Program"},{"id":"https://openalex.org/G530225433","display_name":null,"funder_award_id":"Z201100006820064","funder_id":"https://openalex.org/F4320334978","funder_display_name":"Beijing Nova Program"}],"funders":[{"id":"https://openalex.org/F4320334978","display_name":"Beijing Nova Program","ror":"https://ror.org/034k14f91"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W200744690","https://openalex.org/W1966325234","https://openalex.org/W1994207649","https://openalex.org/W1998174764","https://openalex.org/W2005037128","https://openalex.org/W2009501481","https://openalex.org/W2155328970","https://openalex.org/W2464708700","https://openalex.org/W2560023338","https://openalex.org/W2774320778","https://openalex.org/W2887652137","https://openalex.org/W2898952695","https://openalex.org/W2922901657","https://openalex.org/W2927851116","https://openalex.org/W2945475836","https://openalex.org/W2962778872","https://openalex.org/W2962810718","https://openalex.org/W2964015378","https://openalex.org/W2964227007","https://openalex.org/W2971614929","https://openalex.org/W2979589572","https://openalex.org/W2990368613","https://openalex.org/W2997528981","https://openalex.org/W3014974815","https://openalex.org/W3026779786","https://openalex.org/W3035159724","https://openalex.org/W3088477271","https://openalex.org/W3107399755","https://openalex.org/W3117630903","https://openalex.org/W3156613007","https://openalex.org/W3164981218","https://openalex.org/W3165688950","https://openalex.org/W3179218951","https://openalex.org/W3202117991","https://openalex.org/W3208531740","https://openalex.org/W4210941896","https://openalex.org/W4224244419","https://openalex.org/W4284897204","https://openalex.org/W4285473913","https://openalex.org/W4295917092","https://openalex.org/W4296025769","https://openalex.org/W6738964360","https://openalex.org/W6745316256","https://openalex.org/W6760001035","https://openalex.org/W6778231270","https://openalex.org/W6783243524","https://openalex.org/W6808626977","https://openalex.org/W6847064123"],"related_works":["https://openalex.org/W2762467749","https://openalex.org/W2374048355","https://openalex.org/W2161584192","https://openalex.org/W2359910081","https://openalex.org/W2381929598","https://openalex.org/W2383797864","https://openalex.org/W3024308452","https://openalex.org/W2364351544","https://openalex.org/W2385460613","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Segmentation":[0],"of":[1,13,27,39,54,61,107,143,180,191,219,243,246],"the":[2,10,25,31,40,50,67,78,83,98,108,131,144,150,158],"coronary":[3,14,41,79,99,109,119,145,185,195,240],"artery":[4,42,100,110,120,146,186],"is":[5,21,75,147,177],"an":[6,235],"important":[7],"task":[8],"for":[9,77,96,115],"quantitative":[11],"analysis":[12],"computed":[15],"tomography":[16],"angiography":[17],"(CCTA)":[18],"images":[19,183],"and":[20,36,57,101,113,117,165,212,223,238],"being":[22],"stimulated":[23],"by":[24,130,199],"field":[26],"deep":[28],"learning.":[29],"However,":[30],"complex":[32],"structures":[33],"with":[34,49,149,184,216],"tiny":[35],"narrow":[37],"branches":[38],"bring":[43],"it":[44],"a":[45,70,93,139,217],"great":[46],"challenge.":[47],"Coupled":[48],"medical":[51],"image":[52],"limitations":[53],"low":[55],"resolution":[56],"poor":[58],"contrast,":[59],"fragmentations":[60,245],"segmented":[62,247],"vessels":[63],"frequently":[64],"occur":[65],"in":[66,169],"prediction.":[68],"Therefore,":[69],"geometry-based":[71,159,232],"cascaded":[72,94],"segmentation":[73,160],"method":[74,135,206],"proposed":[76],"artery,":[80,241],"which":[81],"has":[82],"following":[84],"innovations:":[85],"1)":[86],"Integrating":[87],"geometric":[88],"deformation":[89],"networks,":[90],"we":[91],"design":[92],"network":[95],"segmenting":[97],"vectorizing":[102],"results.":[103,229],"The":[104,153,188],"generated":[105,129],"meshes":[106],"are":[111,194],"continuous":[112],"accurate":[114],"twisted":[116],"sophisticated":[118],"structures,":[121],"without":[122],"fragmentations.":[123],"2)":[124],"Different":[125],"from":[126,136],"mesh":[127,142,155],"annotations":[128,198],"traditional":[132],"marching":[133],"cube":[134],"voxel-based":[137],"labels,":[138],"finer":[140],"vectorized":[141],"reconstructed":[148],"regularized":[151],"morphology.":[152],"novel":[154],"annotation":[156],"benefits":[157],"network,":[161],"avoiding":[162],"bifurcation":[163],"adhesion":[164],"point":[166],"cloud":[167],"dispersion":[168],"intricate":[170],"branches.":[171],"3)":[172],"A":[173],"dataset":[174,210],"named":[175],"CCA-200":[176,211,222],"collected,":[178],"consisting":[179],"200":[181,192],"CCTA":[182],"disease.":[187],"ground":[189],"truths":[190],"cases":[193],"internal":[196],"diameter":[197],"professional":[200],"radiologists.":[201],"Extensive":[202],"experiments":[203],"verify":[204],"our":[205,208,231],"on":[207,221,225],"collected":[209],"public":[213],"ASOCA":[214],"dataset,":[215],"Dice":[218],"0.778":[220],"0.895":[224],"ASOCA,":[226],"showing":[227],"superior":[228],"Especially,":[230],"model":[233],"generates":[234],"accurate,":[236],"intact":[237],"smooth":[239],"devoid":[242],"any":[244],"vessels.":[248]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":2}],"updated_date":"2026-08-16T07:02:28.622633","created_date":"2025-10-10T00:00:00"}
