{"id":"https://openalex.org/W2995756761","doi":"https://doi.org/10.1109/ultsym.2019.8925825","title":"Vector Flow Velocity Estimation from Beamsummed Data Using Deep Neural Networks","display_name":"Vector Flow Velocity Estimation from Beamsummed Data Using Deep Neural Networks","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2995756761","doi":"https://doi.org/10.1109/ultsym.2019.8925825","mag":"2995756761"},"language":"en","primary_location":{"id":"doi:10.1109/ultsym.2019.8925825","doi":"https://doi.org/10.1109/ultsym.2019.8925825","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ultsym.2019.8925825","pdf_url":null,"source":{"id":"https://openalex.org/S4393917990","display_name":"IEEE International Ultrasonics Symposium","issn_l":"1948-5719","issn":["1948-5719"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","norway-1"],"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":"2019 IEEE International Ultrasonics Symposium (IUS)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","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/A5100401822","display_name":"You Leo Li","orcid":"https://orcid.org/0000-0002-0447-9819","observed_orcids":["https://orcid.org/0000-0002-0447-9819"]},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"You Leo Li","raw_affiliation_strings":["Department of Radiology, Stanford University, Palo Alto, California, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, Stanford University, Palo Alto, California, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040587139","display_name":"Dongwoon Hyun","orcid":"https://orcid.org/0000-0003-2625-8109","observed_orcids":["https://orcid.org/0000-0003-2625-8109"]},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dongwoon Hyun","raw_affiliation_strings":["Department of Radiology, Stanford University, Palo Alto, California, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, Stanford University, Palo Alto, California, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091413823","display_name":"Jeremy Dahl","orcid":"https://orcid.org/0000-0001-9877-452X","observed_orcids":["https://orcid.org/0000-0001-9877-452X"]},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jeremy J. Dahl","raw_affiliation_strings":["Department of Radiology, Stanford University, Palo Alto, California, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, Stanford University, Palo Alto, California, USA","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":1.514,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.85002895,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"860","last_page":"863"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10727","display_name":"Ultrasound Imaging and Elastography","score":0.9330999851226807,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T10727","display_name":"Ultrasound Imaging and Elastography","score":0.9330999851226807,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.01269999984651804,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.009399999864399433,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/vector-flow-imaging","display_name":"vector flow imaging","score":0.996999979019165},{"id":"https://openalex.org/keywords/flow-velocity-estimation","display_name":"flow velocity estimation","score":0.878000020980835},{"id":"https://openalex.org/keywords/deep-neural-network","display_name":"deep neural network","score":0.9919999837875366},{"id":"https://openalex.org/keywords/doppler-ultrasound","display_name":"Doppler ultrasound","score":0.7120000123977661},{"id":"https://openalex.org/keywords/azimuthal-velocity","display_name":"azimuthal velocity","score":0.4740000069141388},{"id":"https://openalex.org/keywords/axial-velocity","display_name":"axial velocity","score":0.8669999837875366},{"id":"https://openalex.org/keywords/flow-phantom","display_name":"flow phantom","score":0.4490000009536743}],"concepts":[{"id":"https://openalex.org/C20749125","wikidata":"https://www.wikidata.org/wiki/Q7917826","display_name":"Vector flow","level":4,"score":0.737237811088562},{"id":"https://openalex.org/C159737794","wikidata":"https://www.wikidata.org/wiki/Q124274","display_name":"Azimuth","level":2,"score":0.6760196685791016},{"id":"https://openalex.org/C102290492","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle pattern","level":2,"score":0.6580171585083008},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6047655344009399},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5882355570793152},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5462703704833984},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.4776017367839813},{"id":"https://openalex.org/C104293457","wikidata":"https://www.wikidata.org/wiki/Q28324852","display_name":"Imaging phantom","level":2,"score":0.47652968764305115},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4471311569213867},{"id":"https://openalex.org/C166693061","wikidata":"https://www.wikidata.org/wiki/Q5462119","display_name":"Flow velocity","level":3,"score":0.4447416365146637},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4238455295562744},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38604599237442017},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3426447808742523},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.28805896639823914},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.2277144193649292},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.21651342511177063},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20158305764198303},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.16238108277320862},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.13618144392967224}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ultsym.2019.8925825","doi":"https://doi.org/10.1109/ultsym.2019.8925825","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ultsym.2019.8925825","pdf_url":null,"source":{"id":"https://openalex.org/S4393917990","display_name":"IEEE International Ultrasonics Symposium","issn_l":"1948-5719","issn":["1948-5719"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","norway-1"],"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":"2019 IEEE International Ultrasonics Symposium (IUS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W764651262","https://openalex.org/W1513100184","https://openalex.org/W2010807412","https://openalex.org/W2070712157","https://openalex.org/W2081021250","https://openalex.org/W2081359092","https://openalex.org/W2088427193","https://openalex.org/W2136647043","https://openalex.org/W2139553364","https://openalex.org/W2150066425","https://openalex.org/W2158896444","https://openalex.org/W2166343165","https://openalex.org/W2234159546","https://openalex.org/W2514970112","https://openalex.org/W2530689506","https://openalex.org/W2592869698","https://openalex.org/W2620768715","https://openalex.org/W2908486615","https://openalex.org/W2962803115","https://openalex.org/W2963782415","https://openalex.org/W2964123261"],"related_works":["https://openalex.org/W2986582315","https://openalex.org/W2907743567","https://openalex.org/W2514970112","https://openalex.org/W2548857598","https://openalex.org/W2738361667","https://openalex.org/W2770677446","https://openalex.org/W7214284179","https://openalex.org/W3105496763","https://openalex.org/W2012421423","https://openalex.org/W4378070369"],"abstract_inverted_index":{"Vector":[0],"flow":[1,12,35,72,99,137],"imaging":[2],"(VFI)":[3],"is":[4,32,123,130],"a":[5,54,70],"novel":[6],"velocity":[7,13,29,73,100],"measurement":[8],"technique":[9,75,129],"that":[10,31],"provides":[11,28],"information":[14],"in":[15],"both":[16],"azimuth":[17],"and":[18,59,97,105,116,132,136],"axial":[19],"dimensions.":[20],"Compared":[21],"to":[22,110],"conventional":[23],"color":[24],"Doppler":[25],"imaging,":[26],"VFI":[27,38],"estimation":[30,74,101],"independent":[33],"of":[34,118,127],"directions.":[36],"Previous":[37],"techniques":[39],"utilize":[40],"either":[41],"multiple":[42],"transmit":[43],"or":[44,47,49,62],"receive":[45],"beams":[46],"angles,":[48],"speckle":[50],"tracking.":[51],"This":[52],"creates":[53],"trade-off":[55],"between":[56],"computational":[57],"intensity":[58],"estimate":[60],"quality":[61],"equipment":[63],"cost.":[64],"In":[65],"this":[66],"work,":[67],"we":[68],"present":[69],"vector":[71],"based":[76],"on":[77,102],"deep":[78,88],"neural":[79,89,120],"networks":[80],"using":[81,134],"only":[82],"beamsummed":[83],"radio-frequency":[84],"(RF)":[85],"data.":[86],"The":[87,114,125],"network":[90,121],"extracts":[91],"features":[92],"from":[93],"the":[94,103,107,111,119,128],"RF":[95],"data,":[96],"performs":[98],"features,":[104],"maps":[106],"estimates":[108],"back":[109],"spatial":[112],"domain.":[113],"structure":[115],"training":[117],"model":[122],"presented.":[124],"performance":[126],"demonstrated":[131],"evaluated":[133],"simulations":[135],"phantom":[138],"experiments.":[139]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2019-12-26T00:00:00"}
