{"id":"https://openalex.org/W4206750138","doi":"https://doi.org/10.1109/bibm52615.2021.9669523","title":"Shape-aware Multi-task Learning for Semi-supervised 3D Medical Image Segmentation","display_name":"Shape-aware Multi-task Learning for Semi-supervised 3D Medical Image Segmentation","publication_year":2021,"publication_date":"2021-12-09","ids":{"openalex":"https://openalex.org/W4206750138","doi":"https://doi.org/10.1109/bibm52615.2021.9669523"},"language":"en","primary_location":{"id":"doi:10.1109/bibm52615.2021.9669523","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm52615.2021.9669523","pdf_url":null,"source":{"id":"https://openalex.org/S4363607735","display_name":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5100376038","display_name":"Shasha Liu","orcid":"https://orcid.org/0009-0006-0287-8986"},"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":"Shasha Liu","raw_affiliation_strings":["MOE Research Center for Software/Hardware Co-Design Engineering, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"MOE Research Center for Software/Hardware Co-Design Engineering, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101546528","display_name":"Yan Li","orcid":"https://orcid.org/0000-0002-8403-7614"},"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":"Yan Li","raw_affiliation_strings":["MOE Research Center for Software/Hardware Co-Design Engineering, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"MOE Research Center for Software/Hardware Co-Design Engineering, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100631865","display_name":"Xiaohu Li","orcid":"https://orcid.org/0000-0001-8278-3878"},"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":"Xiaohu Li","raw_affiliation_strings":["MOE Research Center for Software/Hardware Co-Design Engineering, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"MOE Research Center for Software/Hardware Co-Design Engineering, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027627793","display_name":"Guitao Cao","orcid":"https://orcid.org/0000-0002-4059-4806"},"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":"Guitao Cao","raw_affiliation_strings":["MOE Research Center for Software/Hardware Co-Design Engineering, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"MOE Research Center for Software/Hardware Co-Design Engineering, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100376038"],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":0.5228,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.77952189,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1418","last_page":"1423"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9997000098228455,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9997000098228455,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9980000257492065,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.8301951885223389},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7963017225265503},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7448979616165161},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6663990020751953},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5680875182151794},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.5049930214881897},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5040613412857056},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5009469985961914},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.49921393394470215},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.4937065541744232},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.4726735055446625},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.47034814953804016},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45744583010673523},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4106981158256531},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.37119540572166443},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.2970585823059082}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8301951885223389},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7963017225265503},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7448979616165161},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6663990020751953},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5680875182151794},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.5049930214881897},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5040613412857056},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5009469985961914},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.49921393394470215},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.4937065541744232},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.4726735055446625},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.47034814953804016},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45744583010673523},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4106981158256531},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37119540572166443},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.2970585823059082},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm52615.2021.9669523","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm52615.2021.9669523","pdf_url":null,"source":{"id":"https://openalex.org/S4363607735","display_name":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1903029394","https://openalex.org/W2600383743","https://openalex.org/W2750925197","https://openalex.org/W2787241931","https://openalex.org/W2891451067","https://openalex.org/W2962914239","https://openalex.org/W2979792663","https://openalex.org/W2979907638","https://openalex.org/W2998663558","https://openalex.org/W3018023895","https://openalex.org/W3024821730","https://openalex.org/W3035665735","https://openalex.org/W3044738063","https://openalex.org/W3083779147","https://openalex.org/W3090844657","https://openalex.org/W3094327244","https://openalex.org/W3095848620","https://openalex.org/W3097499499","https://openalex.org/W3203046931","https://openalex.org/W6735443497","https://openalex.org/W6748692255","https://openalex.org/W6757175246","https://openalex.org/W6776052977","https://openalex.org/W6784903362"],"related_works":["https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W3144569342","https://openalex.org/W4313052709","https://openalex.org/W2945274617","https://openalex.org/W2022929107","https://openalex.org/W2055202857","https://openalex.org/W1999008862","https://openalex.org/W4205800335","https://openalex.org/W2758994127"],"abstract_inverted_index":{"Semi-supervised":[0],"learning":[1,143],"has":[2],"achieved":[3],"many":[4],"successes":[5],"in":[6,115],"medical":[7],"image":[8],"segmentation":[9,56,80,102,130],"since":[10],"it":[11],"reduces":[12],"the":[13,38,65,76,116,129,147,156,173,176,182,198],"costs":[14],"of":[15,149,175],"manually":[16],"annotating":[17],"by":[18],"leveraging":[19],"abundant":[20],"unlabeled":[21,157],"data.":[22],"However,":[23],"these":[24,121],"semi-supervised":[25,55,200],"methods":[26],"lack":[27],"attention":[28],"to":[29,43,63,111,132,161],"ambiguous":[30],"regions":[31],"(e.g.,":[32],"some":[33],"edges":[34],"or":[35],"corners":[36],"around":[37],"targets),":[39],"which":[40],"may":[41],"lead":[42],"meaningless":[44],"and":[45,108,158,165,181,196],"unreliable":[46],"guidance.":[47,167],"In":[48],"this":[49],"paper,":[50],"we":[51,138],"propose":[52],"a":[53,140,163],"novel":[54],"method":[57],"called":[58],"Shape-aware":[59],"Multi-task":[60],"Learning":[61],"(SMTL)":[62],"address":[64],"above":[66],"issue.":[67],"Our":[68],"multi-task":[69,97],"framework":[70,98],"includes":[71],"three":[72],"tasks":[73,124,152],"namely":[74],"i)":[75],"main":[77],"task":[78,84,92],"for":[79,85,93],"ii)":[81],"one":[82],"auxiliary":[83,91,123,151],"signed":[86,104],"distance":[87,105],"regression":[88],"iii)":[89],"another":[90],"contour":[94],"detection.":[95],"The":[96,188],"jointly":[99],"predicts":[100],"probabilistic":[101],"maps,":[103],"maps":[106,110],"(SDMs)":[107],"edge":[109],"collect":[112],"complementary":[113],"information":[114],"existing":[117],"target":[118],"label.":[119],"Specifically,":[120],"two":[122,150],"explicitly":[125],"enforce":[126],"shape-priors":[127],"on":[128,155,172],"output":[131],"generate":[133],"more":[134],"accurate":[135],"masks.":[136],"Moreover,":[137],"design":[139],"region-attention-based":[141],"adversarial":[142],"strategy":[144],"that":[145,191],"enforces":[146],"consistency":[148],"prediction":[153],"distributions":[154],"labeled":[159],"data":[160],"make":[162],"meaningful":[164],"reliable":[166],"We":[168],"evaluate":[169],"our":[170,192],"SMTL":[171,193],"datasets":[174],"2018":[177],"Atrial":[178],"Segmentation":[179,186],"Challenge":[180],"2017":[183],"Liver":[184],"Tumor":[185],"Challenge.":[187],"results":[189],"demonstrate":[190],"achieves":[194],"improvements":[195],"outperforms":[197],"state-of-the-art":[199],"methods.":[201]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
