{"id":"https://openalex.org/W3027445961","doi":"https://doi.org/10.1109/isbi45749.2020.9098666","title":"Self-Supervised Representation Learning for Ultrasound Video","display_name":"Self-Supervised Representation Learning for Ultrasound Video","publication_year":2020,"publication_date":"2020-04-01","ids":{"openalex":"https://openalex.org/W3027445961","doi":"https://doi.org/10.1109/isbi45749.2020.9098666","mag":"3027445961","pmid":"https://pubmed.ncbi.nlm.nih.gov/32489519"},"language":"en","primary_location":{"id":"doi:10.1109/isbi45749.2020.9098666","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi45749.2020.9098666","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7266673","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017599481","display_name":"Jianbo Jiao","orcid":"https://orcid.org/0000-0003-0833-5115"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Jianbo Jiao","raw_affiliation_strings":["Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, UK","Institute of Biomedical Engineering, University of Oxford, UK"],"affiliations":[{"raw_affiliation_string":"Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, UK","institution_ids":["https://openalex.org/I40120149"]},{"raw_affiliation_string":"Institute of Biomedical Engineering, University of Oxford, UK","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039629184","display_name":"Richard Droste","orcid":"https://orcid.org/0000-0002-8030-3321"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Richard Droste","raw_affiliation_strings":["Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, UK","Institute of Biomedical Engineering, University of Oxford, UK"],"affiliations":[{"raw_affiliation_string":"Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, UK","institution_ids":["https://openalex.org/I40120149"]},{"raw_affiliation_string":"Institute of Biomedical Engineering, University of Oxford, UK","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076657548","display_name":"Lior Drukker","orcid":"https://orcid.org/0000-0002-5588-1410"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Lior Drukker","raw_affiliation_strings":["Nuffield Department of Womens & Reproductive Health, University of Oxford, UK","University of Oxford, UK"],"affiliations":[{"raw_affiliation_string":"Nuffield Department of Womens & Reproductive Health, University of Oxford, UK","institution_ids":[]},{"raw_affiliation_string":"University of Oxford, UK","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039160245","display_name":"Aris T. Papageorghiou","orcid":"https://orcid.org/0000-0001-8143-2232"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Aris T. Papageorghiou","raw_affiliation_strings":["Nuffield Department of Womens & Reproductive Health, University of Oxford, UK","University of Oxford, UK"],"affiliations":[{"raw_affiliation_string":"Nuffield Department of Womens & Reproductive Health, University of Oxford, UK","institution_ids":[]},{"raw_affiliation_string":"University of Oxford, UK","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077728082","display_name":"J. Alison Noble","orcid":"https://orcid.org/0000-0002-3060-3772"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"J. Alison Noble","raw_affiliation_strings":["Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, UK","Institute of Biomedical Engineering, University of Oxford, UK"],"affiliations":[{"raw_affiliation_string":"Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, UK","institution_ids":["https://openalex.org/I40120149"]},{"raw_affiliation_string":"Institute of Biomedical Engineering, University of Oxford, UK","institution_ids":["https://openalex.org/I40120149"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5017599481"],"corresponding_institution_ids":["https://openalex.org/I40120149"],"apc_list":null,"apc_paid":null,"fwci":5.3024,"has_fulltext":false,"cited_by_count":51,"citation_normalized_percentile":{"value":0.96324977,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"2020","issue":null,"first_page":"1847","last_page":"1850"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9993000030517578,"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"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9962000250816345,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9954000115394592,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8415921330451965},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6956488490104675},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6559100151062012},{"id":"https://openalex.org/keywords/geometric-transformation","display_name":"Geometric transformation","score":0.5911351442337036},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.5528947710990906},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.5518845915794373},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5516935586929321},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5298854112625122},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4827525019645691},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.46504417061805725},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.46236374974250793},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4528643786907196},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42981404066085815},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3293256163597107}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8415921330451965},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6956488490104675},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6559100151062012},{"id":"https://openalex.org/C56435381","wikidata":"https://www.wikidata.org/wiki/Q1196371","display_name":"Geometric transformation","level":3,"score":0.5911351442337036},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.5528947710990906},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.5518845915794373},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5516935586929321},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5298854112625122},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4827525019645691},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.46504417061805725},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.46236374974250793},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4528643786907196},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42981404066085815},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3293256163597107},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/isbi45749.2020.9098666","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi45749.2020.9098666","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},{"id":"pmid:32489519","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32489519","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":"Proceedings. IEEE International Symposium on Biomedical Imaging","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:7266673","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7266673","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc IEEE Int Symp Biomed Imaging","raw_type":"Text"},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/4e867a9b-502d-4803-8864-9bd2ef58c91f","is_oa":false,"landing_page_url":"https://research.birmingham.ac.uk/en/publications/4e867a9b-502d-4803-8864-9bd2ef58c91f","pdf_url":null,"source":{"id":"https://openalex.org/S4306402634","display_name":"University of Birmingham Research Portal (University of Birmingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79619799","host_organization_name":"University of Birmingham","host_organization_lineage":["https://openalex.org/I79619799"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Jiao, J, Droste, R, Drukker, L, Papageorghiou, A T & Noble, J A 2020, Self-Supervised Representation Learning for Ultrasound Video. in 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)., 9098666, Proceedings - International Symposium on Biomedical Imaging, IEEE, pp. 1847-1850, 17th IEEE International Symposium on Biomedical Imaging, ISBI 2020, Iowa City, United States, 3/04/20. https://doi.org/10.1109/ISBI45749.2020.9098666","raw_type":"contributionToPeriodical"},{"id":"pmh:oai:pure.atira.dk:publications/4e867a9b-502d-4803-8864-9bd2ef58c91f","is_oa":false,"landing_page_url":"https://birmingham.elsevierpure.com/en/publications/4e867a9b-502d-4803-8864-9bd2ef58c91f","pdf_url":null,"source":{"id":"https://openalex.org/S4306402634","display_name":"University of Birmingham Research Portal (University of Birmingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79619799","host_organization_name":"University of Birmingham","host_organization_lineage":["https://openalex.org/I79619799"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Jiao , J , Droste , R , Drukker , L , Papageorghiou , A T & Noble , J A 2020 , Self-Supervised Representation Learning for Ultrasound Video . in 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI) . , 9098666 , Proceedings - International Symposium on Biomedical Imaging , IEEE , pp. 1847-1850 , 17th IEEE International Symposium on Biomedical Imaging, ISBI 2020 , Iowa City , United States , 3/04/20 . https://doi.org/10.1109/ISBI45749.2020.9098666","raw_type":"contributionToPeriodical"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:7266673","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7266673","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc IEEE Int Symp Biomed Imaging","raw_type":"Text"},"sustainable_development_goals":[{"score":0.44999998807907104,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G1277543710","display_name":null,"funder_award_id":"EP/M013774/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W219040644","https://openalex.org/W2326925005","https://openalex.org/W2735582614","https://openalex.org/W2752782242","https://openalex.org/W2891288863","https://openalex.org/W2902644322","https://openalex.org/W2922325549","https://openalex.org/W2946185430","https://openalex.org/W2963420686","https://openalex.org/W2963503775","https://openalex.org/W3101842892","https://openalex.org/W6703437051","https://openalex.org/W6756353443","https://openalex.org/W6762858609"],"related_works":["https://openalex.org/W4295532600","https://openalex.org/W2063823869","https://openalex.org/W2047973478","https://openalex.org/W2067569035","https://openalex.org/W2090985514","https://openalex.org/W3201126466","https://openalex.org/W2145649715","https://openalex.org/W2047313939","https://openalex.org/W2440023763","https://openalex.org/W2962474440"],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,14,50,85],"deep":[3,27],"learning":[4,51,64],"have":[5],"achieved":[6],"promising":[7],"performance":[8],"for":[9,41],"medical":[10,42,73],"image":[11],"analysis,":[12],"while":[13],"most":[15],"cases":[16],"ground-truth":[17],"annotations":[18,32],"from":[19,53,72,98,114],"human":[20,80],"experts":[21],"are":[22,33],"necessary":[23],"to":[24,35,66,87,107,123,142,166],"train":[25],"the":[26,92,99,105,115,119,125,134,138,143,153],"model.":[28],"In":[29,57],"practice,":[30],"such":[31,89],"expensive":[34],"collect":[36],"and":[37,69,132,160,173],"can":[38,156],"be":[39],"scarce":[40],"imaging":[43,74],"applications.":[44],"Therefore,":[45],"there":[46],"is":[47,121],"significant":[48],"interest":[49],"representations":[52,71],"unlabelled":[54,100],"raw":[55],"data.":[56,101],"this":[58],"paper,":[59],"we":[60,103],"propose":[61],"a":[62,90,128],"self-supervised":[63],"approach":[65,155],"learn":[67,88,158],"meaningful":[68,159],"transferable":[70],"video":[75,130,144,150],"without":[76],"any":[77],"type":[78],"of":[79,127],"annotation.":[81],"We":[82],"assume":[83],"that":[84,152],"order":[86,126],"representation,":[91],"model":[93,106,120],"should":[94],"identify":[95],"anatomical":[96],"structures":[97],"Therefore":[102],"force":[104],"address":[108],"anatomy-aware":[109],"tasks":[110,168],"with":[111],"free":[112],"supervision":[113],"data":[116],"itself.":[117],"Specifically,":[118],"designed":[122],"correct":[124],"reshuffled":[129],"clip":[131],"at":[133],"same":[135],"time":[136],"predict":[137],"geometric":[139],"transformation":[140],"applied":[141],"clip.":[145],"Experiments":[146],"on":[147],"fetal":[148],"ultrasound":[149],"show":[151],"proposed":[154],"effectively":[157],"strong":[161],"representations,":[162],"which":[163],"transfer":[164],"well":[165],"downstream":[167],"like":[169],"standard":[170],"plane":[171],"detection":[172],"saliency":[174],"prediction.":[175]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":18},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":5}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}