{"id":"https://openalex.org/W4312689955","doi":"https://doi.org/10.1145/3563737.3563740","title":"Semi-supervised learning with double head approach for carotid artery detection","display_name":"Semi-supervised learning with double head approach for carotid artery detection","publication_year":2022,"publication_date":"2022-08-19","ids":{"openalex":"https://openalex.org/W4312689955","doi":"https://doi.org/10.1145/3563737.3563740"},"language":"en","primary_location":{"id":"doi:10.1145/3563737.3563740","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3563737.3563740","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 7th International Conference on Biomedical Signal and Image Processing (ICBIP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5000127473","display_name":"Zhiwei Li","orcid":"https://orcid.org/0000-0002-2439-5217"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhiwei Li","raw_affiliation_strings":["School of Data Science and Engineering, East China Normal University, China"],"affiliations":[{"raw_affiliation_string":"School of Data Science and Engineering, East China Normal University, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019479187","display_name":"Wei Peng","orcid":"https://orcid.org/0000-0002-2892-5764"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Peng","raw_affiliation_strings":["Information Technology Services, East China Normal University, China"],"affiliations":[{"raw_affiliation_string":"Information Technology Services, East China Normal University, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042455829","display_name":"Changquan Lu","orcid":"https://orcid.org/0000-0001-9849-2688"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changquan Lu","raw_affiliation_strings":["School of Data Science and Engineering, East China Normal University, China"],"affiliations":[{"raw_affiliation_string":"School of Data Science and Engineering, East China Normal University, China","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5000127473"],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2320005,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"12","last_page":"18"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10234","display_name":"Obstructive Sleep Apnea Research","score":0.9718999862670898,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"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/T10234","display_name":"Obstructive Sleep Apnea Research","score":0.9718999862670898,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"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":0.9695000052452087,"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"}},{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","score":0.9692999720573425,"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/computer-science","display_name":"Computer science","score":0.8248133659362793},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7299363613128662},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6500636339187622},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6422602534294128},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6209859848022461},{"id":"https://openalex.org/keywords/head","display_name":"Head (geology)","score":0.5709381103515625},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5384767651557922},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5082063674926758},{"id":"https://openalex.org/keywords/human-head","display_name":"Human head","score":0.46554502844810486},{"id":"https://openalex.org/keywords/carotid-arteries","display_name":"Carotid arteries","score":0.4444522261619568},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4411980211734772},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.4226440191268921},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.41560444235801697},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.09233748912811279},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.06735482811927795}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8248133659362793},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7299363613128662},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6500636339187622},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6422602534294128},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6209859848022461},{"id":"https://openalex.org/C2780312720","wikidata":"https://www.wikidata.org/wiki/Q5689100","display_name":"Head (geology)","level":2,"score":0.5709381103515625},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5384767651557922},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5082063674926758},{"id":"https://openalex.org/C2780549717","wikidata":"https://www.wikidata.org/wiki/Q3409626","display_name":"Human head","level":3,"score":0.46554502844810486},{"id":"https://openalex.org/C2987047532","wikidata":"https://www.wikidata.org/wiki/Q214275","display_name":"Carotid arteries","level":2,"score":0.4444522261619568},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4411980211734772},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.4226440191268921},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.41560444235801697},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.09233748912811279},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.06735482811927795},{"id":"https://openalex.org/C114793014","wikidata":"https://www.wikidata.org/wiki/Q52109","display_name":"Geomorphology","level":1,"score":0.0},{"id":"https://openalex.org/C125287762","wikidata":"https://www.wikidata.org/wiki/Q1758948","display_name":"Absorption (acoustics)","level":2,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3563737.3563740","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3563737.3563740","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 7th International Conference on Biomedical Signal and Image Processing (ICBIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2151103935","https://openalex.org/W2194775991","https://openalex.org/W2920326761","https://openalex.org/W2963091558","https://openalex.org/W2963857746","https://openalex.org/W3035694605","https://openalex.org/W3147929628","https://openalex.org/W4251247712","https://openalex.org/W6603944243","https://openalex.org/W6735463952","https://openalex.org/W6757804589","https://openalex.org/W6765972432"],"related_works":["https://openalex.org/W2801716195","https://openalex.org/W1515733650","https://openalex.org/W4387838477","https://openalex.org/W2004343371","https://openalex.org/W2152840365","https://openalex.org/W1993258123","https://openalex.org/W2067193074","https://openalex.org/W2182785089","https://openalex.org/W4310501991","https://openalex.org/W4312178642"],"abstract_inverted_index":{"The":[0],"detection":[1,66,121],"of":[2,30,33],"carotid":[3,35,64,78],"artery":[4,65,79],"in":[5,24,40,211],"ultrasound":[6,42,82],"medical":[7,54,107],"images":[8,108],"helps":[9],"locating":[10],"other":[11],"organs":[12],"to":[13,21,48,62,76,109,123,188,193],"build":[14],"an":[15],"efficient":[16],"computer-aided":[17],"diagnosis":[18],"system.":[19],"Due":[20],"the":[22,25,34,41,52,84,125,141,162,233],"differences":[23],"speed,":[26],"direction":[27],"and":[28,46,137,152,172,199,217,239],"angle":[29],"continuous":[31],"scanning":[32],"artery,":[36],"its":[37],"imaging":[38],"shape":[39],"image":[43,55],"is":[44,98,158,174],"complex":[45],"easy":[47],"be":[49],"distorted.":[50],"Meanwhile,":[51],"labeled":[53],"datasets":[56],"are":[57,86],"limited.":[58],"So":[59],"it's":[60],"hard":[61],"make":[63,189],"accurately.":[67],"Although":[68],"existing":[69,227],"methods":[70,198],"such":[71],"as":[72],"Mask":[73],"R-CNN":[74],"attempt":[75],"achieve":[77],"segmentation":[80],"by":[81],"data,":[83],"results":[85],"not":[87],"ideal.":[88],"We":[89],"propose":[90],"a":[91,101,145,153],"novel":[92],"architecture":[93,122],"called":[94],"SSL-DH-Faster":[95,207],"RCNN,":[96],"which":[97],"based":[99,160],"on":[100,133,161,169,236],"semi-supervised":[102],"learning":[103],"approach":[104],"using":[105],"unlabeled":[106],"improve":[110,200],"our":[111,115,186,230],"model":[112,201],"performance.":[113],"In":[114],"framework,":[116],"we":[117,181],"adopt":[118],"double":[119],"head":[120,129],"solve":[124],"problem":[126],"that":[127,164,206,224],"single":[128],"structure":[130],"performs":[131],"poorly":[132],"handling":[134],"both":[135],"classification":[136,150,170],"localization":[138,178],"task":[139,151,171],"at":[140],"same":[142],"time.":[143],"Concretely,":[144],"fully":[146],"connected":[147],"head(fc-head)":[148],"for":[149,156,177],"convolution":[154],"head(conv-head)":[155],"regression":[157],"adopted":[159],"reason":[163],"fc-head":[165],"got":[166],"better":[167],"performance":[168,202,235],"conv-head":[173],"more":[175],"suitable":[176],"task.":[179],"Simultaneously,":[180],"combine":[182],"PAFPN":[183],"module":[184],"into":[185],"framework":[187],"low-layer":[190],"information":[191],"easier":[192],"propagate":[194],"with":[195,226],"above":[196],"two":[197],"further.":[203],"Experiments":[204,222],"show":[205,223],"RCNN":[208],"method":[209,231],"proposed":[210],"this":[212],"paper":[213],"achieves":[214,232],"superior":[215],"performance,":[216],"outperforms":[218],"several":[219],"popular":[220,228],"methods.":[221],"compared":[225],"methods,":[229],"best":[234],"AP50,":[237],"AP75":[238],"[email":[240],"protected][0.50:0.95]":[241],"metrics.":[242]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}