{"id":"https://openalex.org/W7166722904","doi":"https://doi.org/10.48550/arxiv.2606.30082","title":"Clinical Risk-Aware Multi-Level Grading for Coronary Artery Stenosis through Curved Feature Reconstruction","display_name":"Clinical Risk-Aware Multi-Level Grading for Coronary Artery Stenosis through Curved Feature Reconstruction","publication_year":2026,"publication_date":"2026-06-29","ids":{"openalex":"https://openalex.org/W7166722904","doi":"https://doi.org/10.48550/arxiv.2606.30082"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.30082","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.30082","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"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.2606.30082","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101250546","display_name":"Shishuang Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Shishuang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139673359","display_name":"Hongtai Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Hongtai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101764765","display_name":"Junjie Hou","orcid":"https://orcid.org/0009-0006-3754-1021"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hou, Junjie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139669258","display_name":"Yuhang Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yuhang","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":0.5742999911308289,"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":0.5742999911308289,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.13429999351501465,"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":0.09969999641180038,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/coronary-artery-disease","display_name":"Coronary artery disease","score":0.5349000096321106},{"id":"https://openalex.org/keywords/stenosis","display_name":"Stenosis","score":0.5327000021934509},{"id":"https://openalex.org/keywords/grading","display_name":"Grading (engineering)","score":0.5202999711036682},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5045999884605408},{"id":"https://openalex.org/keywords/clinical-significance","display_name":"Clinical significance","score":0.41839998960494995},{"id":"https://openalex.org/keywords/artery","display_name":"Artery","score":0.3952000141143799},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38909998536109924}],"concepts":[{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.6779000163078308},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6588000059127808},{"id":"https://openalex.org/C2778213512","wikidata":"https://www.wikidata.org/wiki/Q844935","display_name":"Coronary artery disease","level":2,"score":0.5349000096321106},{"id":"https://openalex.org/C2780007028","wikidata":"https://www.wikidata.org/wiki/Q2343082","display_name":"Stenosis","level":2,"score":0.5327000021934509},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.5277000069618225},{"id":"https://openalex.org/C2777286243","wikidata":"https://www.wikidata.org/wiki/Q5591926","display_name":"Grading (engineering)","level":2,"score":0.5202999711036682},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5045999884605408},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43290001153945923},{"id":"https://openalex.org/C63363279","wikidata":"https://www.wikidata.org/wiki/Q5133848","display_name":"Clinical significance","level":2,"score":0.41839998960494995},{"id":"https://openalex.org/C2776820930","wikidata":"https://www.wikidata.org/wiki/Q9655","display_name":"Artery","level":2,"score":0.3952000141143799},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38909998536109924},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3783000111579895},{"id":"https://openalex.org/C2779974597","wikidata":"https://www.wikidata.org/wiki/Q28448986","display_name":"Clinical Practice","level":2,"score":0.34929999709129333},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.34049999713897705},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.33329999446868896},{"id":"https://openalex.org/C2777987666","wikidata":"https://www.wikidata.org/wiki/Q1440572","display_name":"Fractional flow reserve","level":4,"score":0.31869998574256897},{"id":"https://openalex.org/C2993012660","wikidata":"https://www.wikidata.org/wiki/Q18185","display_name":"Grading scale","level":2,"score":0.31619998812675476},{"id":"https://openalex.org/C2778902805","wikidata":"https://www.wikidata.org/wiki/Q322177","display_name":"Ablation","level":2,"score":0.3012999892234802},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.29109999537467957},{"id":"https://openalex.org/C194789388","wikidata":"https://www.wikidata.org/wiki/Q17855283","display_name":"CAD","level":2,"score":0.271699994802475},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.26330000162124634}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.30082","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.30082","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.30082","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.30082","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"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":{"Developing":[0],"a":[1,109,127,158],"multi-level":[2,24],"grading":[3],"model":[4],"for":[5,13],"coronary":[6,17],"artery":[7,18],"stenosis":[8,71],"holds":[9],"great":[10],"clinical":[11,77,136,152],"significance":[12],"the":[14,50,84,90,95,140,145,151,175],"diagnosis":[15],"of":[16,53,177],"disease.":[19],"However,":[20],"designing":[21],"an":[22],"effective":[23],"deep":[25],"learning":[26],"algorithm":[27,85,146],"faces":[28],"significant":[29],"challenges.":[30],"Specifically,":[31],"utilizing":[32],"CCTA":[33,42,124],"or":[34],"3D":[35,57,121],"SCPR":[36,58,122],"images":[37,43,59],"alone":[38],"presents":[39],"inherent":[40],"shortcomings:":[41],"are":[44,60,73],"difficult":[45],"to":[46,49,62,113,134],"analyze":[47],"due":[48],"tortuous":[51],"paths":[52],"blood":[54],"vessels,":[55],"while":[56],"prone":[61],"abnormal":[63],"distortions":[64],"that":[65,144,162],"hinder":[66],"accurate":[67],"grading.":[68],"Furthermore,":[69],"different":[70],"grades":[72],"associated":[74],"with":[75,150],"varying":[76],"risks,":[78],"and":[79,107,116,123,169],"incorporating":[80],"this":[81],"association":[82],"into":[83,139],"is":[86,132],"non-trivial.":[87],"To":[88],"address":[89],"former":[91],"problems,":[92],"we":[93],"propose":[94],"Curved":[96],"Feature":[97],"Reconstruction":[98],"(CFR)":[99],"module,":[100],"which":[101],"uses":[102],"vessel":[103],"curves":[104],"as":[105],"prior":[106],"employs":[108],"point-by-point":[110],"correspondence":[111],"strategy":[112],"precisely":[114],"align":[115,149],"fuse":[117],"features":[118],"from":[119],"both":[120],"images.":[125],"Meanwhile,":[126],"Clinical":[128],"Risk-Aware":[129],"(CR)":[130],"Loss":[131],"employed":[133],"introduce":[135],"risk":[137],"relevance":[138],"network":[141],"training":[142],"so":[143],"can":[147],"better":[148],"diagnosis.":[153],"The":[154],"experimental":[155],"results":[156],"on":[157],"in-house":[159],"dataset":[160],"reveal":[161],"our":[163,178],"approach":[164],"significantly":[165],"outperforms":[166],"other":[167],"methods,":[168],"several":[170],"ablation":[171],"studies":[172],"also":[173],"demonstrate":[174],"effectiveness":[176],"proposed":[179],"designs.":[180]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-01T00:00:00"}