{"id":"https://openalex.org/W2994886866","doi":"https://doi.org/10.1007/s00521-019-04646-3","title":"Real-time diameter of the fetal aorta from ultrasound","display_name":"Real-time diameter of the fetal aorta from ultrasound","publication_year":2019,"publication_date":"2019-12-18","ids":{"openalex":"https://openalex.org/W2994886866","doi":"https://doi.org/10.1007/s00521-019-04646-3","mag":"2994886866","pmid":"https://pubmed.ncbi.nlm.nih.gov/32523256"},"language":"en","primary_location":{"id":"doi:10.1007/s00521-019-04646-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00521-019-04646-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00521-019-04646-3.pdf","source":{"id":"https://openalex.org/S147897268","display_name":"Neural Computing and Applications","issn_l":"0941-0643","issn":["0941-0643","1433-3058"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computing and Applications","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s00521-019-04646-3.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050968498","display_name":"Nicol\u00f3 Savioli","orcid":"https://orcid.org/0000-0002-3382-0422"},"institutions":[{"id":"https://openalex.org/I183935753","display_name":"King's College London","ror":"https://ror.org/0220mzb33","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I183935753"]},{"id":"https://openalex.org/I4210119896","display_name":"King's College School","ror":"https://ror.org/02bbqcn27","country_code":"GB","type":"education","lineage":["https://openalex.org/I4210119896"]},{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Nicol\u00f3 Savioli","raw_affiliation_strings":["Department of Biomedical Engineering, King's College London, London, SE1 7EH UK","Department of Computing, Imperial College London, Huxley Building, 180 Queen's Gate, London, SW7 2RH UK","Department of Biomedical Engineering, King's College London, London, SE1 7EH, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, King's College London, London, SE1 7EH UK","institution_ids":["https://openalex.org/I183935753","https://openalex.org/I4210119896"]},{"raw_affiliation_string":"Department of Computing, Imperial College London, Huxley Building, 180 Queen's Gate, London, SW7 2RH UK","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"Department of Biomedical Engineering, King's College London, London, SE1 7EH, UK","institution_ids":["https://openalex.org/I183935753"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022937331","display_name":"Enrico Grisan","orcid":"https://orcid.org/0000-0002-7365-5652"},"institutions":[{"id":"https://openalex.org/I138689650","display_name":"University of Padua","ror":"https://ror.org/00240q980","country_code":"IT","type":"education","lineage":["https://openalex.org/I138689650"]},{"id":"https://openalex.org/I183935753","display_name":"King's College London","ror":"https://ror.org/0220mzb33","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I183935753"]},{"id":"https://openalex.org/I4210119896","display_name":"King's College School","ror":"https://ror.org/02bbqcn27","country_code":"GB","type":"education","lineage":["https://openalex.org/I4210119896"]}],"countries":["GB","IT"],"is_corresponding":false,"raw_author_name":"Enrico Grisan","raw_affiliation_strings":["Department of Biomedical Engineering, King's College London, London, SE1 7EH UK","Department of Information Engineering, University of Padova, Padova, Italy","Department of Biomedical Engineering, King's College London, London, SE1 7EH, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, King's College London, London, SE1 7EH UK","institution_ids":["https://openalex.org/I183935753","https://openalex.org/I4210119896"]},{"raw_affiliation_string":"Department of Information Engineering, University of Padova, Padova, Italy","institution_ids":["https://openalex.org/I138689650"]},{"raw_affiliation_string":"Department of Biomedical Engineering, King's College London, London, SE1 7EH, UK","institution_ids":["https://openalex.org/I183935753"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058919438","display_name":"Silvia Visentin","orcid":"https://orcid.org/0000-0002-1079-7098"},"institutions":[{"id":"https://openalex.org/I138689650","display_name":"University of Padua","ror":"https://ror.org/00240q980","country_code":"IT","type":"education","lineage":["https://openalex.org/I138689650"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Silvia Visentin","raw_affiliation_strings":["Department of Woman and Child Health, University Hospital of Padova, Padova, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Woman and Child Health, University Hospital of Padova, Padova, Italy","institution_ids":["https://openalex.org/I138689650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057527492","display_name":"Erich Cosmi","orcid":"https://orcid.org/0000-0002-3010-2206"},"institutions":[{"id":"https://openalex.org/I138689650","display_name":"University of Padua","ror":"https://ror.org/00240q980","country_code":"IT","type":"education","lineage":["https://openalex.org/I138689650"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Erich Cosmi","raw_affiliation_strings":["Department of Woman and Child Health, University Hospital of Padova, Padova, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Woman and Child Health, University Hospital of Padova, Padova, Italy","institution_ids":["https://openalex.org/I138689650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010581004","display_name":"Giovanni Montana","orcid":"https://orcid.org/0000-0003-3942-3900"},"institutions":[{"id":"https://openalex.org/I183935753","display_name":"King's College London","ror":"https://ror.org/0220mzb33","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I183935753"]},{"id":"https://openalex.org/I39555362","display_name":"University of Warwick","ror":"https://ror.org/01a77tt86","country_code":"GB","type":"education","lineage":["https://openalex.org/I39555362"]},{"id":"https://openalex.org/I4210119896","display_name":"King's College School","ror":"https://ror.org/02bbqcn27","country_code":"GB","type":"education","lineage":["https://openalex.org/I4210119896"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Giovanni Montana","raw_affiliation_strings":["Department of Biomedical Engineering, King's College London, London, SE1 7EH UK","WMG International Digital Laboratory, University of Warwick, Coventry, CV32 7AL UK","Department of Biomedical Engineering, King's College London, London, SE1 7EH, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, King's College London, London, SE1 7EH UK","institution_ids":["https://openalex.org/I183935753","https://openalex.org/I4210119896"]},{"raw_affiliation_string":"WMG International Digital Laboratory, University of Warwick, Coventry, CV32 7AL UK","institution_ids":["https://openalex.org/I39555362"]},{"raw_affiliation_string":"Department of Biomedical Engineering, King's College London, London, SE1 7EH, UK","institution_ids":["https://openalex.org/I183935753"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085599943","display_name":"Pablo Lamata","orcid":"https://orcid.org/0000-0002-3097-4928"},"institutions":[{"id":"https://openalex.org/I183935753","display_name":"King's College London","ror":"https://ror.org/0220mzb33","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I183935753"]},{"id":"https://openalex.org/I4210119896","display_name":"King's College School","ror":"https://ror.org/02bbqcn27","country_code":"GB","type":"education","lineage":["https://openalex.org/I4210119896"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Pablo Lamata","raw_affiliation_strings":["Department of Biomedical Engineering, King's College London, London, SE1 7EH UK","Department of Biomedical Engineering, King's College London, London, SE1 7EH, UK"],"raw_orcid":"https://orcid.org/0000-0002-3097-4928","affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, King's College London, London, SE1 7EH UK","institution_ids":["https://openalex.org/I183935753","https://openalex.org/I4210119896"]},{"raw_affiliation_string":"Department of Biomedical Engineering, King's College London, London, SE1 7EH, UK","institution_ids":["https://openalex.org/I183935753"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5085599943"],"corresponding_institution_ids":["https://openalex.org/I183935753","https://openalex.org/I4210119896"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":0.1937,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.63020045,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"32","issue":"11","first_page":"6735","last_page":"6744"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10290","display_name":"Pregnancy and preeclampsia studies","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/2729","display_name":"Obstetrics and Gynecology"},"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/T10290","display_name":"Pregnancy and preeclampsia studies","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/2729","display_name":"Obstetrics and Gynecology"},"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":0.9807999730110168,"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/T11184","display_name":"Neonatal and fetal brain pathology","score":0.9599999785423279,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7469479441642761},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7339897155761719},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5917930603027344},{"id":"https://openalex.org/keywords/ultrasound","display_name":"Ultrasound","score":0.5838437080383301},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5406962633132935},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5389062166213989},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.513027548789978},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.4904007911682129},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.44740158319473267},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44383227825164795},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3804659843444824},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3602573871612549},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19987794756889343},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12688705325126648},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1115027368068695},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.09014230966567993}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7469479441642761},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7339897155761719},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5917930603027344},{"id":"https://openalex.org/C143753070","wikidata":"https://www.wikidata.org/wiki/Q162564","display_name":"Ultrasound","level":2,"score":0.5838437080383301},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5406962633132935},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5389062166213989},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.513027548789978},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4904007911682129},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.44740158319473267},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44383227825164795},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3804659843444824},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3602573871612549},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19987794756889343},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12688705325126648},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1115027368068695},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.09014230966567993},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1007/s00521-019-04646-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00521-019-04646-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00521-019-04646-3.pdf","source":{"id":"https://openalex.org/S147897268","display_name":"Neural Computing and Applications","issn_l":"0941-0643","issn":["0941-0643","1433-3058"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computing and Applications","raw_type":"journal-article"},{"id":"pmid:32523256","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32523256","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":"Neural computing & applications","raw_type":null},{"id":"pmh:oai:kclpure.kcl.ac.uk:publications/9a58dd02-7385-4bc3-8b91-44a44fe50b83","is_oa":true,"landing_page_url":"https://kclpure.kcl.ac.uk/portal/en/publications/9a58dd02-7385-4bc3-8b91-44a44fe50b83","pdf_url":"https://kclpure.kcl.ac.uk/ws/files/124208496/Real_time_diameter_of_the_SAVIOLI_Accepted22November2019_ePublished18December2019_GOLD_VoR_CC_BY_.pdf","source":{"id":"https://openalex.org/S4306400216","display_name":"Research Portal (King's College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I183935753","host_organization_name":"King's College London","host_organization_lineage":["https://openalex.org/I183935753"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Savioli, N, Grisan, E, Visentin, S, Cosmi, E, Montana, G & Lamata, P 2019, 'Real-time diameter of the fetal aorta from ultrasound', NEURAL COMPUTING AND APPLICATIONS. https://doi.org/10.1007/s00521-019-04646-3","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:pubmedcentral.nih.gov:7260154","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7260154","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Neural Comput Appl","raw_type":"Text"},{"id":"pmh:oai:www.research.unipd.it:11577/3324414","is_oa":true,"landing_page_url":"http://hdl.handle.net/11577/3324414","pdf_url":null,"source":{"id":"https://openalex.org/S4377196283","display_name":"Research Padua  Archive (University of Padua)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I138689650","host_organization_name":"University of Padua","host_organization_lineage":["https://openalex.org/I138689650"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1007/s00521-019-04646-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00521-019-04646-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00521-019-04646-3.pdf","source":{"id":"https://openalex.org/S147897268","display_name":"Neural Computing and Applications","issn_l":"0941-0643","issn":["0941-0643","1433-3058"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computing and Applications","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.6100000143051147,"display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G1322964166","display_name":null,"funder_award_id":"203148/Z/16/Z","funder_id":"https://openalex.org/F4320311904","funder_display_name":"Wellcome Trust"},{"id":"https://openalex.org/G339059223","display_name":null,"funder_award_id":"Z/17/Z","funder_id":"https://openalex.org/F4320311904","funder_display_name":"Wellcome Trust"},{"id":"https://openalex.org/G5399234883","display_name":"Unravelling the physics of the pressure drop in blood flow constrictions","funder_award_id":"209450","funder_id":"https://openalex.org/F4320311904","funder_display_name":"Wellcome Trust"},{"id":"https://openalex.org/G5746980720","display_name":null,"funder_award_id":"209450/Z/17","funder_id":"https://openalex.org/F4320311904","funder_display_name":"Wellcome Trust"},{"id":"https://openalex.org/G5907639349","display_name":"King's College London Medical Engineering Centre of Research Excellence","funder_award_id":"203148","funder_id":"https://openalex.org/F4320311904","funder_display_name":"Wellcome Trust"},{"id":"https://openalex.org/G8124921036","display_name":null,"funder_award_id":"209450/Z/17/Z","funder_id":"https://openalex.org/F4320311904","funder_display_name":"Wellcome Trust"},{"id":"https://openalex.org/G8270365688","display_name":null,"funder_award_id":"209450/Z/17/Z","funder_id":"https://openalex.org/F4320307874","funder_display_name":"Wellcome"}],"funders":[{"id":"https://openalex.org/F4320307874","display_name":"Wellcome","ror":"https://ror.org/029chgv08"},{"id":"https://openalex.org/F4320311904","display_name":"Wellcome Trust","ror":"https://ror.org/029chgv08"},{"id":"https://openalex.org/F4320320285","display_name":"King's College London","ror":"https://ror.org/0220mzb33"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"},{"id":"https://openalex.org/F4320337314","display_name":"Centre For Medical Engineering, King\u2019s College London","ror":"https://ror.org/04s9kfd63"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2994886866.pdf","grobid_xml":"https://content.openalex.org/works/W2994886866.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1531884058","https://openalex.org/W1965274263","https://openalex.org/W1979027860","https://openalex.org/W1998305775","https://openalex.org/W2017491825","https://openalex.org/W2035038939","https://openalex.org/W2044993603","https://openalex.org/W2079201249","https://openalex.org/W2125598970","https://openalex.org/W2129488169","https://openalex.org/W2141039492","https://openalex.org/W2149164488","https://openalex.org/W2163605009","https://openalex.org/W2274287116","https://openalex.org/W2293422822","https://openalex.org/W2294318823","https://openalex.org/W2475079525","https://openalex.org/W2561675875","https://openalex.org/W2567234109","https://openalex.org/W2592929672","https://openalex.org/W2768828870","https://openalex.org/W2790251179","https://openalex.org/W2799339739","https://openalex.org/W2885878352","https://openalex.org/W2892576650","https://openalex.org/W2962889061","https://openalex.org/W2963446712","https://openalex.org/W2963515175","https://openalex.org/W2964121744","https://openalex.org/W2964350391"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4375867731","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W2964954556","https://openalex.org/W3029198973","https://openalex.org/W3019910406"],"abstract_inverted_index":{"Abstract":[0],"The":[1,93,153,197],"automatic":[2],"analysis":[3],"of":[4,12,25,30,45,56,70,89,100,118,150,174,201,205],"ultrasound":[5,36,102],"sequences":[6,103],"can":[7],"substantially":[8,164],"improve":[9],"the":[10,22,27,31,54,67,71,87,90,106,116,134,158,175,202],"efficiency":[11],"clinical":[13,215],"diagnosis.":[14],"This":[15],"article":[16],"presents":[17],"an":[18,162,171],"attempt":[19],"to":[20,81,166,182,195],"automate":[21],"challenging":[23],"task":[24],"measuring":[26],"vascular":[28],"diameter":[29],"fetal":[32],"abdominal":[33],"aorta":[34],"from":[35,179,193],"images.":[37],"We":[38],"propose":[39],"a":[40,48,59,74,98,124,147,189],"neural":[41,50],"network":[42,51],"architecture":[43],"consisting":[44],"three":[46],"blocks:":[47],"convolutional":[49],"(CNN)":[52],"for":[53,65,213],"extraction":[55,117],"imaging":[57],"features,":[58,119],"convolution":[60],"gated":[61],"recurrent":[62],"unit":[63],"(C-GRU)":[64],"exploiting":[66],"temporal":[68],"redundancy":[69],"signal,":[72],"and":[73,110,136,188],"regularized":[75],"loss":[76],"function,":[77],"called":[78],"CyclicLoss":[79],",":[80,187],"impose":[82],"our":[83],"prior":[84],"knowledge":[85],"about":[86],"periodicity":[88],"observed":[91],"signal.":[92],"solution":[94],"is":[95,121],"investigated":[96],"with":[97,111,132,157],"cohort":[99],"25":[101],"acquired":[104],"during":[105],"third-trimester":[107],"pregnancy":[108],"check,":[109],"1000":[112],"synthetic":[113,137],"sequences.":[114],"In":[115],"it":[120,211],"shown":[122],"that":[123,140],"shallow":[125,159],"CNN":[126,151],"outperforms":[127],"two":[128],"other":[129],"deep":[130],"CNNs":[131],"both":[133],"real":[135],"cohorts,":[138],"suggesting":[139],"echocardiographic":[141],"features":[142],"are":[143],"optimally":[144],"captured":[145],"by":[146],"reduced":[148],"number":[149],"layers.":[152],"proposed":[154,203],"architecture,":[155],"working":[156],"CNN,":[160],"reaches":[161],"accuracy":[163],"superior":[165],"previously":[167],"reported":[168],"methods,":[169],"providing":[170],"average":[172],"reduction":[173,192],"mean":[176,198],"squared":[177],"error":[178,191],"0.31":[180],"(state-of-the-art)":[181],"0.09":[183],"$$\\mathrm{mm}^2$$":[184],"<mml:math":[185],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"><mml:msup><mml:mrow><mml:mi>mm</mml:mi></mml:mrow><mml:mn>2</mml:mn></mml:msup></mml:math>":[186],"relative":[190],"8.1":[194],"5.3%.":[196],"execution":[199],"speed":[200],"approach":[204],"289":[206],"frames":[207],"per":[208],"second":[209],"makes":[210],"suitable":[212],"real-time":[214],"use.":[216]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-16T07:32:37.131356","created_date":"2025-10-10T00:00:00"}
