{"id":"https://openalex.org/W4224989643","doi":"https://doi.org/10.1109/isbi52829.2022.9761613","title":"A Machine Learning Framework for Fully Automatic 3D Fetal Cardiac Ultrasound Evaluation","display_name":"A Machine Learning Framework for Fully Automatic 3D Fetal Cardiac Ultrasound Evaluation","publication_year":2022,"publication_date":"2022-03-28","ids":{"openalex":"https://openalex.org/W4224989643","doi":"https://doi.org/10.1109/isbi52829.2022.9761613"},"language":"en","primary_location":{"id":"doi:10.1109/isbi52829.2022.9761613","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi52829.2022.9761613","pdf_url":null,"source":{"id":"https://openalex.org/S4363605129","display_name":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","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":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","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/A5075009305","display_name":"Manna E. Philip","orcid":null},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Manna E. Philip","raw_affiliation_strings":["UNSW,School of Computer Science and Engineering,Sydney,Australia","School of Computer Science and Engineering, UNSW, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"UNSW,School of Computer Science and Engineering,Sydney,Australia","institution_ids":["https://openalex.org/I31746571"]},{"raw_affiliation_string":"School of Computer Science and Engineering, UNSW, Sydney, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030462449","display_name":"Ana Ferrieira","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ana Ferrieira","raw_affiliation_strings":["UNSW,School of Womens&#x2019; &amp; Childrens&#x2019; Health, Faculty of Medicine,Australia"],"affiliations":[{"raw_affiliation_string":"UNSW,School of Womens&#x2019; &amp; Childrens&#x2019; Health, Faculty of Medicine,Australia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037839491","display_name":"Aishani Tomar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aishani Tomar","raw_affiliation_strings":["UNSW,School of Womens&#x2019; &amp; Childrens&#x2019; Health, Faculty of Medicine,Australia"],"affiliations":[{"raw_affiliation_string":"UNSW,School of Womens&#x2019; &amp; Childrens&#x2019; Health, Faculty of Medicine,Australia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062248783","display_name":"Sparsh Chawla","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sparsh Chawla","raw_affiliation_strings":["UNSW,School of Womens&#x2019; &amp; Childrens&#x2019; Health, Faculty of Medicine,Australia"],"affiliations":[{"raw_affiliation_string":"UNSW,School of Womens&#x2019; &amp; Childrens&#x2019; Health, Faculty of Medicine,Australia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052453301","display_name":"Alec Welsh","orcid":"https://orcid.org/0000-0002-7389-0513"},"institutions":[{"id":"https://openalex.org/I2799851941","display_name":"Royal Hospital for Women","ror":"https://ror.org/021cxfs56","country_code":"AU","type":"healthcare","lineage":["https://openalex.org/I2799851941","https://openalex.org/I4210147382"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Alec W. Welsh","raw_affiliation_strings":["UNSW,School of Womens&#x2019; &amp; Childrens&#x2019; Health, Faculty of Medicine,Australia","Department of Maternal-Fetal Medicine, Royal Hospital for Women, Randwick, Australia"],"affiliations":[{"raw_affiliation_string":"UNSW,School of Womens&#x2019; &amp; Childrens&#x2019; Health, Faculty of Medicine,Australia","institution_ids":[]},{"raw_affiliation_string":"Department of Maternal-Fetal Medicine, Royal Hospital for Women, Randwick, Australia","institution_ids":["https://openalex.org/I2799851941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030399979","display_name":"Gordon Stevenson","orcid":"https://orcid.org/0000-0002-2809-8084"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gordon N. Stevenson","raw_affiliation_strings":["UNSW,School of Womens&#x2019; &amp; Childrens&#x2019; Health, Faculty of Medicine,Australia"],"affiliations":[{"raw_affiliation_string":"UNSW,School of Womens&#x2019; &amp; Childrens&#x2019; Health, Faculty of Medicine,Australia","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055952724","display_name":"Arcot Sowmya","orcid":"https://orcid.org/0000-0001-9236-5063"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Arcot Sowmya","raw_affiliation_strings":["UNSW,School of Computer Science and Engineering,Sydney,Australia","School of Computer Science and Engineering, UNSW, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"UNSW,School of Computer Science and Engineering,Sydney,Australia","institution_ids":["https://openalex.org/I31746571"]},{"raw_affiliation_string":"School of Computer Science and Engineering, UNSW, Sydney, Australia","institution_ids":["https://openalex.org/I31746571"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5075009305"],"corresponding_institution_ids":["https://openalex.org/I31746571"],"apc_list":null,"apc_paid":null,"fwci":0.6061,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.58474576,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12552","display_name":"Fetal and Pediatric Neurological Disorders","score":0.9973999857902527,"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":0.9973999857902527,"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/T10300","display_name":"Congenital Heart Disease Studies","score":0.9869999885559082,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.9545999765396118,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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":0.7532682418823242},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6953014135360718},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6886491775512695},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6308373212814331},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6245182752609253},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5066807866096497},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4685457944869995},{"id":"https://openalex.org/keywords/dice","display_name":"Dice","score":0.4282672703266144},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41014426946640015}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7532682418823242},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6953014135360718},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6886491775512695},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6308373212814331},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6245182752609253},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5066807866096497},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4685457944869995},{"id":"https://openalex.org/C22029948","wikidata":"https://www.wikidata.org/wiki/Q45089","display_name":"Dice","level":2,"score":0.4282672703266144},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41014426946640015},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi52829.2022.9761613","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi52829.2022.9761613","pdf_url":null,"source":{"id":"https://openalex.org/S4363605129","display_name":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","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":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320315885","display_name":"Australian Government","ror":"https://ror.org/0314h5y94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2039207139","https://openalex.org/W2127890285","https://openalex.org/W2141200055","https://openalex.org/W2148347694","https://openalex.org/W2162318554","https://openalex.org/W2556177465","https://openalex.org/W2590958578","https://openalex.org/W2666230004","https://openalex.org/W2892117886","https://openalex.org/W2907750714","https://openalex.org/W2910211359","https://openalex.org/W2958958034","https://openalex.org/W2962914239","https://openalex.org/W3094502228","https://openalex.org/W3203841574","https://openalex.org/W4212875960","https://openalex.org/W6639824700","https://openalex.org/W6660455074","https://openalex.org/W6730104353","https://openalex.org/W6754615942","https://openalex.org/W6784333009","https://openalex.org/W6791637211"],"related_works":["https://openalex.org/W3104750253","https://openalex.org/W3021239166","https://openalex.org/W2586273397","https://openalex.org/W2390936256","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Fetal":[0],"cardiac":[1,91],"ultrasound":[2,80],"(US)":[3],"is":[4,138],"an":[5,39,83],"understudied":[6],"but":[7],"important":[8],"area":[9],"of":[10,20,65,89,146],"medical":[11],"image":[12],"analysis.":[13],"In":[14],"this":[15,33],"work,":[16],"we":[17],"identify":[18],"sources":[19],"error":[21],"and":[22,137],"obstacles":[23],"that":[24],"may":[25],"render":[26],"artificial":[27],"intelligence":[28],"(AI)":[29],"models":[30],"ineffective":[31],"in":[32,105,144,150],"particular":[34],"setting.":[35],"We":[36,57,100],"then":[37],"present":[38],"efficient":[40],"AI":[41],"segmentation":[42,92],"pipeline":[43],"for":[44,111,121],"the":[45,106,131,135,147,151],"fetal":[46,90],"heart":[47],"using":[48,73,94],"raw":[49],"3D-US":[50,67],"volume":[51],"data":[52,85,132],"with":[53],"no":[54],"prior":[55],"processing.":[56],"applied":[58],"our":[59],"work":[60],"on":[61,77,130],"a":[62,102],"dataset":[63],"consisting":[64],"30":[66],"volumes":[68],"from":[69],"26":[70],"participants,":[71],"acquired":[72],"3":[74],"different":[75,79],"probes":[76],"2":[78],"machines.":[81],"Using":[82],"appropriate":[84],"enhancement":[86],"schema,":[87],"performance":[88,143],"improves":[93],"state-of-the-art":[95],"deep":[96],"learning":[97,127],"(DL)":[98],"methods.":[99],"obtained":[101],"19%":[103],"increase":[104,118],"Dice":[107],"Similarity":[108],"Coefficient":[109],"(DSC)":[110],"convolutional":[112],"neural":[113],"networks":[114],"(CNN).":[115],"A":[116],"16%":[117],"was":[119],"observed":[120],"transformer":[122],"based":[123],"networks.":[124],"The":[125],"machine":[126],"framework":[128],"focuses":[129],"rather":[133],"than":[134],"method,":[136],"able":[139],"to":[140],"achieve":[141],"good":[142],"spite":[145],"numerous":[148],"variations":[149],"dataset.":[152]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
