{"id":"https://openalex.org/W2984562136","doi":"https://doi.org/10.1109/access.2019.2950387","title":"Deep Learning-Based Methodology for Recognition of Fetal Brain Standard Scan Planes in 2D Ultrasound Images","display_name":"Deep Learning-Based Methodology for Recognition of Fetal Brain Standard Scan Planes in 2D Ultrasound Images","publication_year":2019,"publication_date":"2019-10-30","ids":{"openalex":"https://openalex.org/W2984562136","doi":"https://doi.org/10.1109/access.2019.2950387","mag":"2984562136"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2950387","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2950387","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08887441.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08887441.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088144923","display_name":"Ruowei Qu","orcid":"https://orcid.org/0000-0001-7534-7840"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruowei Qu","raw_affiliation_strings":["State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0001-7534-7840","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100737468","display_name":"Guizhi Xu","orcid":"https://orcid.org/0000-0002-9637-0051"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guizhi Xu","raw_affiliation_strings":["State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008119474","display_name":"Chunxia Ding","orcid":"https://orcid.org/0009-0002-2719-8259"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chunxia Ding","raw_affiliation_strings":["Ultrasound Department, Zhangjiakou Maternal and Child Health Hospital, Hebei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ultrasound Department, Zhangjiakou Maternal and Child Health Hospital, Hebei, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019369617","display_name":"Wenyan Jia","orcid":"https://orcid.org/0009-0009-2260-0975"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wenyan Jia","raw_affiliation_strings":["Laboratory for Computational Neuroscience, University of Pittsburgh, Pittsburgh, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory for Computational Neuroscience, University of Pittsburgh, Pittsburgh, USA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103248296","display_name":"Mingui Sun","orcid":"https://orcid.org/0000-0001-7948-9205"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mingui Sun","raw_affiliation_strings":["Laboratory for Computational Neuroscience, University of Pittsburgh, Pittsburgh, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory for Computational Neuroscience, University of Pittsburgh, Pittsburgh, USA","institution_ids":["https://openalex.org/I170201317"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":5.1265,"has_fulltext":true,"cited_by_count":50,"citation_normalized_percentile":{"value":0.95176113,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"8","issue":null,"first_page":"44443","last_page":"44451"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12552","display_name":"Fetal and Pediatric Neurological Disorders","score":0.978600025177002,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"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/T12552","display_name":"Fetal and Pediatric Neurological Disorders","score":0.978600025177002,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9717000126838684,"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":0.9556000232696533,"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/computer-science","display_name":"Computer science","score":0.6734694242477417},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.63694828748703},{"id":"https://openalex.org/keywords/ultrasound","display_name":"Ultrasound","score":0.5294346809387207},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4525711238384247},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4348873496055603},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4206628203392029},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.2709692120552063},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1622009575366974}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6734694242477417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.63694828748703},{"id":"https://openalex.org/C143753070","wikidata":"https://www.wikidata.org/wiki/Q162564","display_name":"Ultrasound","level":2,"score":0.5294346809387207},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4525711238384247},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4348873496055603},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4206628203392029},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.2709692120552063},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1622009575366974}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2950387","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2950387","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08887441.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:3f3731bf4d4c452ea2631a17a6d12828","is_oa":true,"landing_page_url":"https://doaj.org/article/3f3731bf4d4c452ea2631a17a6d12828","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 44443-44451 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2950387","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2950387","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08887441.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.4300000071525574,"display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G7694314791","display_name":"\u57fa\u4e8e\u6df1\u90e8\u7ecf\u9885\u78c1\u523a\u6fc0\u7684\u5c40\u90e8\u573a\u7535\u4f4d\u7279\u5f81\u5206\u6790\u53ca\u7f51\u7edc\u8c03\u63a7\u673a\u5236\u7814\u7a76","funder_award_id":"51677053","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G909452483","display_name":"\u57fa\u4e8e\u591a\u5c3a\u5ea6\u878d\u5408\u7684\u7ecf\u9885\u78c1\u523a\u6fc0\u5bf9\u5b66\u4e60\u8bb0\u5fc6\u5f71\u54cd\u7684\u673a\u5236\u7814\u7a76","funder_award_id":"51737003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324851","display_name":"Hebei University","ror":"https://ror.org/01p884a79"},{"id":"https://openalex.org/F4320326691","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08"},{"id":"https://openalex.org/F4320330487","display_name":"State Key Laboratory of Reliability and Intelligence of Electrical Equipment","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2984562136.pdf","grobid_xml":"https://content.openalex.org/works/W2984562136.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W22026586","https://openalex.org/W50483400","https://openalex.org/W190746659","https://openalex.org/W1606858007","https://openalex.org/W1905882502","https://openalex.org/W1964856489","https://openalex.org/W1988819287","https://openalex.org/W1993882792","https://openalex.org/W2012592962","https://openalex.org/W2012743205","https://openalex.org/W2013733580","https://openalex.org/W2026514485","https://openalex.org/W2034842090","https://openalex.org/W2045902838","https://openalex.org/W2061715187","https://openalex.org/W2063540402","https://openalex.org/W2068061882","https://openalex.org/W2084985476","https://openalex.org/W2107167693","https://openalex.org/W2119249988","https://openalex.org/W2148471708","https://openalex.org/W2149933564","https://openalex.org/W2159498975","https://openalex.org/W2159511100","https://openalex.org/W2160815625","https://openalex.org/W2163605009","https://openalex.org/W2167536222","https://openalex.org/W2294318823","https://openalex.org/W2555486686","https://openalex.org/W2600174524","https://openalex.org/W2919115771","https://openalex.org/W2963758027","https://openalex.org/W3016413756","https://openalex.org/W3097096317","https://openalex.org/W4285719527","https://openalex.org/W4299518610","https://openalex.org/W6682132143","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407"],"abstract_inverted_index":{"Two-dimensional":[0],"ultrasound":[1,175],"scanning":[2],"(US)":[3],"has":[4],"become":[5],"a":[6,143,193],"highly":[7],"recommended":[8],"examination":[9],"in":[10,13,87,243],"prenatal":[11],"diagnosis":[12,33],"many":[14],"countries.":[15],"Accurate":[16],"detection":[17],"of":[18,56,63,73,77,90,96,138,162,172,239],"abnormalities":[19],"and":[20,34,45,83,105,149,182,214],"correct":[21],"fetal":[22,74,91,97,139],"brain":[23,92,98],"standard":[24,81,136],"planes":[25,82,137],"is":[26,65,142,153,200],"the":[27,37,61,70,88,94,115,150,160,201,208,216,226,236],"most":[28],"necessary":[29],"precondition":[30],"for":[31],"successful":[32],"measurement.":[35],"In":[36,118],"past":[38],"few":[39],"years,":[40],"support":[41],"vector":[42],"machine":[43,47],"(SVM)":[44],"other":[46,84,151,229],"learning":[48,232],"methods":[49,125],"have":[50],"been":[51],"devoted":[52],"to":[53,69,114,132],"automatic":[54],"recognition":[55,64,89,116],"2D":[57,174],"ultrasonic":[58],"images,":[59,93,189],"but":[60],"performance":[62,161],"not":[66],"satisfactory":[67],"due":[68],"wide":[71],"diversity":[72],"postures,":[75],"shortage":[76],"data,":[78],"similarities":[79],"between":[80,180],"reasons.":[85],"Especially":[86],"features":[95],"images":[99,176],"such":[100],"as":[101],"shape,":[102],"texture,":[103],"color":[104],"others":[106],"are":[107],"very":[108],"similar,":[109],"which":[110,199],"presents":[111],"great":[112,237],"challenges":[113],"work.":[117],"this":[119,244],"study,":[120],"we":[121,165],"proposed":[122,209],"two":[123,167],"main":[124],"based":[126,218],"on":[127,219],"deep":[128,144,220,231],"convolutional":[129,145,221,240],"neural":[130,146,222,241],"networks":[131,223,242],"automatically":[133],"recognize":[134],"six":[135],"brains.":[140],"One":[141],"network":[147],"(CNN),":[148],"one":[152],"CNN-based":[154],"domain":[155],"transfer":[156],"learning.":[157],"To":[158],"examine":[159],"these":[163],"algorithms,":[164],"constructed":[166],"datasets.":[168],"Dataset":[169,185],"1":[170],"consists":[171],"30,000":[173],"from":[177,192],"155":[178],"subjects":[179],"16":[181],"34":[183],"weeks.":[184],"2,":[186],"containing":[187],"1,200":[188],"was":[190],"acquired":[191],"research":[194],"participant":[195],"throughout":[196],"40":[197],"weeks,":[198],"entire":[202],"pregnancy.":[203],"Experimental":[204],"results":[205,213],"show":[206],"that":[207,215],"solutions":[210],"achieve":[211],"promising":[212],"frameworks":[217],"generally":[224],"outperform":[225],"ones":[227],"using":[228],"classical":[230],"methods,":[233],"thus":[234],"demonstrating":[235],"potential":[238],"area.":[245]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
