{"id":"https://openalex.org/W4399849667","doi":"https://doi.org/10.1371/journal.pcbi.1012231","title":"Image2Flow: A proof-of-concept hybrid image and graph convolutional neural network for rapid patient-specific pulmonary artery segmentation and CFD flow field calculation from 3D cardiac MRI data","display_name":"Image2Flow: A proof-of-concept hybrid image and graph convolutional neural network for rapid patient-specific pulmonary artery segmentation and CFD flow field calculation from 3D cardiac MRI data","publication_year":2024,"publication_date":"2024-06-20","ids":{"openalex":"https://openalex.org/W4399849667","doi":"https://doi.org/10.1371/journal.pcbi.1012231"},"language":"en","primary_location":{"id":"doi:10.1371/journal.pcbi.1012231","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pcbi.1012231","pdf_url":"https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1012231&type=printable","source":{"id":"https://openalex.org/S86033158","display_name":"PLoS Computational Biology","issn_l":"1553-734X","issn":["1553-734X","1553-7358"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS Computational Biology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1012231&type=printable","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080873035","display_name":"Tina Yao","orcid":"https://orcid.org/0000-0003-0470-311X"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Tina Yao","raw_affiliation_strings":["Institute of Cardiovascular Science, University College London, London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Institute of Cardiovascular Science, University College London, London, United Kingdom","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055422240","display_name":"Endrit Pajaziti","orcid":"https://orcid.org/0000-0003-1185-2973"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Endrit Pajaziti","raw_affiliation_strings":["Institute of Cardiovascular Science, University College London, London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Institute of Cardiovascular Science, University College London, London, United Kingdom","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004452392","display_name":"Michael A. Quail","orcid":"https://orcid.org/0000-0002-7005-4720"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Michael Quail","raw_affiliation_strings":["Institute of Cardiovascular Science, University College London, London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Institute of Cardiovascular Science, University College London, London, United Kingdom","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013642105","display_name":"Silvia Schievano","orcid":null},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Silvia Schievano","raw_affiliation_strings":["Institute of Cardiovascular Science, University College London, London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Institute of Cardiovascular Science, University College London, London, United Kingdom","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035508703","display_name":"Jennifer A. Steeden","orcid":"https://orcid.org/0000-0002-9792-2022"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Jennifer Steeden","raw_affiliation_strings":["Institute of Cardiovascular Science, University College London, London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Institute of Cardiovascular Science, University College London, London, United Kingdom","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065376456","display_name":"Vivek Muthurangu","orcid":"https://orcid.org/0000-0002-4292-6456"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Vivek Muthurangu","raw_affiliation_strings":["Institute of Cardiovascular Science, University College London, London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Institute of Cardiovascular Science, University College London, London, United Kingdom","institution_ids":["https://openalex.org/I45129253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5004452392","https://openalex.org/A5013642105","https://openalex.org/A5035508703","https://openalex.org/A5055422240","https://openalex.org/A5065376456","https://openalex.org/A5080873035"],"corresponding_institution_ids":["https://openalex.org/I45129253"],"apc_list":{"value":2655,"currency":"USD","value_usd":2655},"apc_paid":{"value":2655,"currency":"USD","value_usd":2655},"fwci":3.2192,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.92743025,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"20","issue":"6","first_page":"e1012231","last_page":"e1012231"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10821","display_name":"Cardiovascular Function and Risk Factors","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/T10821","display_name":"Cardiovascular Function and Risk Factors","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/T10172","display_name":"Cardiac Valve Diseases and Treatments","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/T10193","display_name":"Coronary Interventions and Diagnostics","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/computational-fluid-dynamics","display_name":"Computational fluid dynamics","score":0.7049432992935181},{"id":"https://openalex.org/keywords/polygon-mesh","display_name":"Polygon mesh","score":0.6803756952285767},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6178763508796692},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5426249504089355},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5210539698600769},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5158349871635437},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4661475419998169},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11815300583839417}],"concepts":[{"id":"https://openalex.org/C1633027","wikidata":"https://www.wikidata.org/wiki/Q815820","display_name":"Computational fluid dynamics","level":2,"score":0.7049432992935181},{"id":"https://openalex.org/C31487907","wikidata":"https://www.wikidata.org/wiki/Q1154597","display_name":"Polygon mesh","level":2,"score":0.6803756952285767},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6178763508796692},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5426249504089355},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5210539698600769},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5158349871635437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4661475419998169},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11815300583839417},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1371/journal.pcbi.1012231","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pcbi.1012231","pdf_url":"https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1012231&type=printable","source":{"id":"https://openalex.org/S86033158","display_name":"PLoS Computational Biology","issn_l":"1553-734X","issn":["1553-734X","1553-7358"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS Computational Biology","raw_type":"journal-article"},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:10196663","is_oa":true,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/10196663/","pdf_url":"https://discovery.ucl.ac.uk/id/eprint/10196663/1/Image2Flow%20A%20proof-of-concept%20hybrid%20image%20and%20graph%20convolutional%20neural%20network%20for%20rapid%20patient-specific%20pulmonary%20arter.pdf","source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"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":"   PLoS Computational Biology , 20  (6)    , Article e1012231. (2024)      ","raw_type":"Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:11218942","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11218942","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11218942/pdf/pcbi.1012231.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"PLoS Comput Biol","raw_type":"Text"},{"id":"pmh:oai:RePEc:plo:pcbi00:1012231","is_oa":false,"landing_page_url":"https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1012231","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},{"id":"pmh:oai:doaj.org/article:b62a9605cdd34e1997af8d04cb3db56d","is_oa":true,"landing_page_url":"https://doaj.org/article/b62a9605cdd34e1997af8d04cb3db56d","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"PLoS Computational Biology, Vol 20, Iss 6, p e1012231 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1371/journal.pcbi.1012231","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pcbi.1012231","pdf_url":"https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1012231&type=printable","source":{"id":"https://openalex.org/S86033158","display_name":"PLoS Computational Biology","issn_l":"1553-734X","issn":["1553-734X","1553-7358"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS Computational Biology","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5099999904632568,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[{"id":"https://openalex.org/G2488100534","display_name":null,"funder_award_id":"EP/S021612/1, MR/S032290/1","funder_id":"https://openalex.org/F4320314731","funder_display_name":"UK Research and Innovation"},{"id":"https://openalex.org/G2591455603","display_name":null,"funder_award_id":"RG2661/17/20","funder_id":"https://openalex.org/F4320320036","funder_display_name":"Heart Research UK"},{"id":"https://openalex.org/G3547576634","display_name":null,"funder_award_id":"S032290","funder_id":"https://openalex.org/F4320319992","funder_display_name":"British Heart Foundation"},{"id":"https://openalex.org/G3946957574","display_name":null,"funder_award_id":"EP/N02124X/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G3985079780","display_name":null,"funder_award_id":"EP/S021612/1","funder_id":"https://openalex.org/F4320314731","funder_display_name":"UK Research and Innovation"},{"id":"https://openalex.org/G6234596480","display_name":null,"funder_award_id":"PG/17/6/32797","funder_id":"https://openalex.org/F4320319992","funder_display_name":"British Heart Foundation"},{"id":"https://openalex.org/G8300814543","display_name":null,"funder_award_id":"NH/18/1/33511, PG/17/6/32797","funder_id":"https://openalex.org/F4320319992","funder_display_name":"British Heart Foundation"},{"id":"https://openalex.org/G905572971","display_name":null,"funder_award_id":"G/17/6/32797","funder_id":"https://openalex.org/F4320319992","funder_display_name":"British Heart Foundation"}],"funders":[{"id":"https://openalex.org/F4320314731","display_name":"UK Research and Innovation","ror":"https://ror.org/001aqnf71"},{"id":"https://openalex.org/F4320319992","display_name":"British Heart Foundation","ror":"https://ror.org/02wdwnk04"},{"id":"https://openalex.org/F4320320036","display_name":"Heart Research UK","ror":"https://ror.org/04j68sw28"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4399849667.pdf"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W127494906","https://openalex.org/W1156422488","https://openalex.org/W1987512289","https://openalex.org/W2004947597","https://openalex.org/W2044652637","https://openalex.org/W2058493851","https://openalex.org/W2063398772","https://openalex.org/W2137147119","https://openalex.org/W2147673683","https://openalex.org/W2172897761","https://openalex.org/W2195908889","https://openalex.org/W2464078935","https://openalex.org/W2532627760","https://openalex.org/W2604944342","https://openalex.org/W2754405648","https://openalex.org/W2803419220","https://openalex.org/W2966333895","https://openalex.org/W2990240688","https://openalex.org/W3009563704","https://openalex.org/W3101612813","https://openalex.org/W3122725681","https://openalex.org/W3130872505","https://openalex.org/W4287753834","https://openalex.org/W4288938035","https://openalex.org/W4295747938","https://openalex.org/W4306160174","https://openalex.org/W4308060166","https://openalex.org/W4308295841","https://openalex.org/W4366817211","https://openalex.org/W4387188008","https://openalex.org/W4388275554","https://openalex.org/W4388805587"],"related_works":["https://openalex.org/W1557607869","https://openalex.org/W2366350639","https://openalex.org/W2087496541","https://openalex.org/W2028455732","https://openalex.org/W4313703117","https://openalex.org/W2085564391","https://openalex.org/W1984758362","https://openalex.org/W2042049060","https://openalex.org/W2992936613","https://openalex.org/W1997160662"],"abstract_inverted_index":{"Computational":[0],"fluid":[1],"dynamics":[2],"(CFD)":[3],"can":[4],"be":[5],"used":[6,60],"for":[7,110,200],"non-invasive":[8],"evaluation":[9],"of":[10,42,152,157,169,190],"hemodynamics.":[11],"However,":[12],"its":[13],"routine":[14],"use":[15],"is":[16,237,262],"limited":[17],"by":[18],"labor-intensive":[19],"manual":[20,267],"segmentation,":[21,153],"CFD":[22,54,85,136,159,258],"mesh":[23],"creation,":[24],"and":[25,51,69,81,93,113,119,135,154,202,209,227,246,248,257],"time-consuming":[26],"simulation.":[27],"This":[28,57,230],"study":[29,59,232],"aims":[30],"to":[31,37,99,126,132,171,173,220,239],"train":[32],"a":[33,67,116,128,139,186,274],"deep":[34],"learning":[35],"model":[36],"both":[38,66],"generate":[39],"patient-specific":[40,133,242],"volume-meshes":[41],"the":[43,76,101,155,167],"pulmonary":[44,73,129],"artery":[45,130],"from":[46,65],"3D":[47,62],"cardiac":[48,63],"MRI":[49],"data":[50],"directly":[52],"estimate":[53],"flow":[55,249],"fields.":[56],"proof-of-concept":[58,231],"135":[61],"MRIs":[64,77],"public":[68],"private":[70],"dataset.":[71,104],"The":[72,105,194],"arteries":[74],"in":[75,150,259,273],"were":[78,87],"manually":[79],"segmented":[80],"converted":[82],"into":[83],"volume-meshes.":[84],"simulations":[86],"performed":[88],"on":[89],"ground":[90,102],"truth":[91,103],"meshes":[92,98],"interpolated":[94],"onto":[95],"point-point":[96],"correspondent":[97],"create":[100],"dataset":[106],"was":[107,124,148,160,177,205],"split":[108],"110/10/15":[109],"training,":[111],"validation,":[112],"testing.":[114],"Image2Flow,":[115],"hybrid":[117],"image":[118],"graph":[120],"convolutional":[121],"neural":[122],"network,":[123],"trained":[125],"transform":[127],"template":[131],"anatomy":[134],"values,":[137],"taking":[138],"specific":[140],"inlet":[141,175,222],"velocity":[142,203,228],"as":[143],"an":[144,217],"additional":[145],"input.":[146],"Image2Flow":[147,170,180,214,254],"evaluated":[149],"terms":[151],"accuracy":[156,184],"predicted":[158],"assessed":[161],"using":[162,252],"node-wise":[163,196],"comparisons.":[164],"In":[165],"addition,":[166],"ability":[168],"respond":[172],"increasing":[174,225],"velocities":[176,223],"also":[178,215],"evaluated.":[179],"achieved":[181],"excellent":[182],"segmentation":[183,245,256],"with":[185,224],"median":[187,195],"Dice":[188],"score":[189],"0.91":[191],"(IQR:":[192,207,211],"0.86\u20130.92).":[193],"normalized":[197],"absolute":[198],"error":[199],"pressure":[201,226,247],"magnitude":[204],"11.75%":[206],"9.60\u201315.30%)":[208],"9.90%":[210],"8.47\u201311.90),":[212],"respectively.":[213],"showed":[216],"expected":[218],"response":[219],"increased":[221],"values.":[229],"has":[233],"shown":[234],"that":[235],"it":[236,270],"possible":[238],"simultaneously":[240],"perform":[241],"volume-mesh":[243],"based":[244],"field":[250],"estimation":[251],"Image2Flow.":[253],"completes":[255],"~330ms,":[260],"which":[261],"~5000":[263],"times":[264],"faster":[265],"than":[266],"methods,":[268],"making":[269],"more":[271],"feasible":[272],"clinical":[275],"environment.":[276]},"counts_by_year":[{"year":2025,"cited_by_count":8}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2024-06-21T00:00:00"}