{"id":"https://openalex.org/W4313624533","doi":"https://doi.org/10.3389/fdata.2022.1080715","title":"3D bi-directional transformer U-Net for medical image segmentation","display_name":"3D bi-directional transformer U-Net for medical image segmentation","publication_year":2023,"publication_date":"2023-01-06","ids":{"openalex":"https://openalex.org/W4313624533","doi":"https://doi.org/10.3389/fdata.2022.1080715","pmid":"https://pubmed.ncbi.nlm.nih.gov/36687770"},"language":"en","primary_location":{"id":"doi:10.3389/fdata.2022.1080715","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fdata.2022.1080715","pdf_url":"https://www.frontiersin.org/articles/10.3389/fdata.2022.1080715/pdf","source":{"id":"https://openalex.org/S4210201220","display_name":"Frontiers in Big Data","issn_l":"2624-909X","issn":["2624-909X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.frontiersin.org/articles/10.3389/fdata.2022.1080715/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084242782","display_name":"Xiyao Fu","orcid":"https://orcid.org/0000-0002-5854-150X"},"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":"Xiyao Fu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, United States","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076206341","display_name":"Zhexian Sun","orcid":"https://orcid.org/0000-0003-1225-182X"},"institutions":[{"id":"https://openalex.org/I204465549","display_name":"Washington University in St. Louis","ror":"https://ror.org/01yc7t268","country_code":"US","type":"education","lineage":["https://openalex.org/I204465549"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhexian Sun","raw_affiliation_strings":["Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, United States","institution_ids":["https://openalex.org/I204465549"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079922796","display_name":"Haoteng Tang","orcid":"https://orcid.org/0000-0003-0323-1755"},"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":true,"raw_author_name":"Haoteng Tang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, United States","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056032220","display_name":"Eric M. Zou","orcid":"https://orcid.org/0000-0002-6994-9439"},"institutions":[{"id":"https://openalex.org/I2802642760","display_name":"Montgomery High School","ror":"https://ror.org/02hc4dw24","country_code":"US","type":"education","lineage":["https://openalex.org/I2802642760"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eric M. Zou","raw_affiliation_strings":["Montgomery Blair High School Maryland, 51 University Blvd E, Silver Spring, MD, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Montgomery Blair High School Maryland, 51 University Blvd E, Silver Spring, MD, United States","institution_ids":["https://openalex.org/I2802642760"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060016795","display_name":"Heng Huang","orcid":"https://orcid.org/0000-0002-3483-8333"},"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":"Heng Huang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, United States","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100424542","display_name":"Yong Wang","orcid":"https://orcid.org/0000-0003-3366-3137"},"institutions":[{"id":"https://openalex.org/I204465549","display_name":"Washington University in St. Louis","ror":"https://ror.org/01yc7t268","country_code":"US","type":"education","lineage":["https://openalex.org/I204465549"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yong Wang","raw_affiliation_strings":["Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, United States","Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO, United States","Department of Obstetrics and Gynecology, Washington University in St. Louis, St. Louis, MO, United States","Department of Radiology, Washington University in St. Louis, St. Louis, MO, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, United States","institution_ids":["https://openalex.org/I204465549"]},{"raw_affiliation_string":"Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO, United States","institution_ids":["https://openalex.org/I204465549"]},{"raw_affiliation_string":"Department of Obstetrics and Gynecology, Washington University in St. Louis, St. Louis, MO, United States","institution_ids":["https://openalex.org/I204465549"]},{"raw_affiliation_string":"Department of Radiology, Washington University in St. Louis, St. Louis, MO, United States","institution_ids":["https://openalex.org/I204465549"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001309013","display_name":"Liang Zhan","orcid":"https://orcid.org/0000-0002-7920-4828"},"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":true,"raw_author_name":"Liang Zhan","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, United States","institution_ids":["https://openalex.org/I170201317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5001309013","https://openalex.org/A5079922796"],"corresponding_institution_ids":["https://openalex.org/I170201317"],"apc_list":{"value":1150,"currency":"USD","value_usd":1150},"apc_paid":{"value":1181,"currency":"EUR","value_usd":1273},"fwci":1.5936,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.85119335,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"5","issue":null,"first_page":"1080715","last_page":"1080715"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9995999932289124,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.9987000226974487,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7895920276641846},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7785710692405701},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7276145815849304},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.7095978260040283},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6620993614196777},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.632140040397644},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6097207069396973},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.59788578748703},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.46981245279312134},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42561596632003784},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3863091468811035},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.09332621097564697}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7895920276641846},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7785710692405701},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7276145815849304},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.7095978260040283},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6620993614196777},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.632140040397644},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6097207069396973},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.59788578748703},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.46981245279312134},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42561596632003784},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3863091468811035},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.09332621097564697},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3389/fdata.2022.1080715","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fdata.2022.1080715","pdf_url":"https://www.frontiersin.org/articles/10.3389/fdata.2022.1080715/pdf","source":{"id":"https://openalex.org/S4210201220","display_name":"Frontiers in Big Data","issn_l":"2624-909X","issn":["2624-909X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Big Data","raw_type":"journal-article"},{"id":"pmid:36687770","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36687770","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":"Frontiers in big data","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:9853518","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9853518","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC9853518/pdf/fdata-05-1080715.pdf","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":"Front Big Data","raw_type":"Text"},{"id":"pmh:oai:digitalcommons.wustl.edu:oa_4-3544","is_oa":true,"landing_page_url":"https://digitalcommons.wustl.edu/oa_4/2562","pdf_url":null,"source":{"id":"https://openalex.org/S4306400764","display_name":"Digital Commons@Becker (Washington University School of Medicine)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I204465549","host_organization_name":"Washington University in St. Louis","host_organization_lineage":["https://openalex.org/I204465549"],"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":"2020-Current year OA Pubs","raw_type":"text"},{"id":"pmh:oai:doaj.org/article:57c56f18592d45ac9859c6df19a91d12","is_oa":true,"landing_page_url":"https://doaj.org/article/57c56f18592d45ac9859c6df19a91d12","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":"Frontiers in Big Data, Vol 5 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3389/fdata.2022.1080715","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fdata.2022.1080715","pdf_url":"https://www.frontiersin.org/articles/10.3389/fdata.2022.1080715/pdf","source":{"id":"https://openalex.org/S4210201220","display_name":"Frontiers in Big Data","issn_l":"2624-909X","issn":["2624-909X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Big Data","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5199999809265137,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[{"id":"https://openalex.org/G1742171491","display_name":null,"funder_award_id":"1548562","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G2206590661","display_name":null,"funder_award_id":"ACI-1548562","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G2909726059","display_name":"CAREER: Brain Imaging Genetics via multimodal modular structure querying","funder_award_id":"2045848","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3206248822","display_name":null,"funder_award_id":"IIS 2045848","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G367708065","display_name":null,"funder_award_id":"ACI-1548562","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3709464396","display_name":null,"funder_award_id":"-1548562","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3730782400","display_name":null,"funder_award_id":"1548562","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3756250311","display_name":null,"funder_award_id":"INV-005417, INV-035476, and INV-037302","funder_id":"https://openalex.org/F4320306137","funder_display_name":"Bill and Melinda Gates Foundation"},{"id":"https://openalex.org/G3853842951","display_name":null,"funder_award_id":"INV-035476","funder_id":"https://openalex.org/F4320306137","funder_display_name":"Bill and Melinda Gates Foundation"},{"id":"https://openalex.org/G4355318821","display_name":null,"funder_award_id":"INV-037302","funder_id":"https://openalex.org/F4320306137","funder_display_name":"Bill and Melinda Gates Foundation"},{"id":"https://openalex.org/G4897854425","display_name":null,"funder_award_id":"grant number ACI-1548562","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4940394123","display_name":null,"funder_award_id":"NGP10119","funder_id":"https://openalex.org/F4320306133","funder_display_name":"Burroughs Wellcome Fund"},{"id":"https://openalex.org/G5514976981","display_name":null,"funder_award_id":"COVID-19","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G5567452398","display_name":null,"funder_award_id":"INV-005417","funder_id":"https://openalex.org/F4320306137","funder_display_name":"Bill and Melinda Gates Foundation"},{"id":"https://openalex.org/G5926293910","display_name":null,"funder_award_id":"R01HD094381","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G5959462937","display_name":null,"funder_award_id":"R01HD094381","funder_id":"https://openalex.org/F4320337611","funder_display_name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development"},{"id":"https://openalex.org/G6129859679","display_name":null,"funder_award_id":"R01HD104822","funder_id":"https://openalex.org/F4320337611","funder_display_name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development"},{"id":"https://openalex.org/G7368192814","display_name":null,"funder_award_id":"R01HD104822","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G7404166632","display_name":"Bridges: From Communities and Data to Workflows and Insight","funder_award_id":"1445606","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7992884429","display_name":null,"funder_award_id":"ACI-1445606","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G8729765517","display_name":null,"funder_award_id":"ACI-1445606","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8907196067","display_name":null,"funder_award_id":"-1548562","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306133","display_name":"Burroughs Wellcome Fund","ror":"https://ror.org/01d35cw23"},{"id":"https://openalex.org/F4320306137","display_name":"Bill and Melinda Gates Foundation","ror":"https://ror.org/0456r8d26"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320332884","display_name":"McDonnell Center for Systems Neuroscience","ror":"https://ror.org/01yc7t268"},{"id":"https://openalex.org/F4320337611","display_name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","ror":"https://ror.org/04byxyr05"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4313624533.pdf"},"referenced_works_count":65,"referenced_works":["https://openalex.org/W146900863","https://openalex.org/W2064675550","https://openalex.org/W2163605009","https://openalex.org/W2395611524","https://openalex.org/W2464708700","https://openalex.org/W2612690371","https://openalex.org/W2791282053","https://openalex.org/W2890779863","https://openalex.org/W2896457183","https://openalex.org/W2962835968","https://openalex.org/W2963840672","https://openalex.org/W2963881378","https://openalex.org/W2964199361","https://openalex.org/W2996290406","https://openalex.org/W3007268491","https://openalex.org/W3009813469","https://openalex.org/W3014974815","https://openalex.org/W3015788359","https://openalex.org/W3094502228","https://openalex.org/W3108591672","https://openalex.org/W3112701542","https://openalex.org/W3115781494","https://openalex.org/W3127751679","https://openalex.org/W3134565071","https://openalex.org/W3160284783","https://openalex.org/W3168491317","https://openalex.org/W3176628328","https://openalex.org/W3192079976","https://openalex.org/W3198035652","https://openalex.org/W3200379731","https://openalex.org/W3204364267","https://openalex.org/W4221163766","https://openalex.org/W4224985589","https://openalex.org/W4226409718","https://openalex.org/W4234552385","https://openalex.org/W4238965627","https://openalex.org/W4281754077","https://openalex.org/W4281902802","https://openalex.org/W4296129249","https://openalex.org/W4301409532","https://openalex.org/W4318566866","https://openalex.org/W4321438308","https://openalex.org/W4384924424","https://openalex.org/W6637573526","https://openalex.org/W6639824700","https://openalex.org/W6640054144","https://openalex.org/W6684191040","https://openalex.org/W6687483927","https://openalex.org/W6734716764","https://openalex.org/W6739901393","https://openalex.org/W6746102887","https://openalex.org/W6746507118","https://openalex.org/W6748481559","https://openalex.org/W6754309021","https://openalex.org/W6756344431","https://openalex.org/W6761752162","https://openalex.org/W6763509872","https://openalex.org/W6775709611","https://openalex.org/W6791241316","https://openalex.org/W6791469159","https://openalex.org/W6791637211","https://openalex.org/W6791764970","https://openalex.org/W6792038723","https://openalex.org/W6794715132","https://openalex.org/W6798616986"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4375867731","https://openalex.org/W4390516098","https://openalex.org/W2181948922","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":{"As":[0],"one":[1],"of":[2,55,75,80,86,108,177],"the":[3,52,77,84,106,148,157],"popular":[4],"deep":[5,8],"learning":[6],"methods,":[7,102],"convolutional":[9],"neural":[10],"networks":[11,82],"(DCNNs)":[12],"have":[13,21,47],"been":[14,48],"widely":[15],"adopted":[16],"in":[17,26,36,138,195],"segmentation":[18,27,123,131,193],"tasks":[19],"and":[20,99,119,142,156,180],"received":[22],"positive":[23],"feedback.":[24],"However,":[25],"tasks,":[28],"DCNN-based":[29],"frameworks":[30],"are":[31,59],"known":[32],"for":[33,116,127],"their":[34],"incompetence":[35],"dealing":[37],"with":[38,68,93],"global":[39,53,100],"relations":[40],"within":[41],"imaging":[42],"features.":[43],"Although":[44],"several":[45,191],"techniques":[46],"proposed":[49,120],"to":[50,63,96],"enhance":[51],"reasoning":[54,101],"DCNN,":[56],"these":[57],"models":[58],"either":[60],"not":[61,73],"able":[62],"gain":[64],"satisfying":[65],"performances":[66],"compared":[67,92],"traditional":[69],"fully-convolutional":[70],"structures":[71],"or":[72],"capable":[74],"utilizing":[76],"basic":[78],"advantages":[79],"CNN-based":[81],"(namely":[83],"ability":[85,107],"local":[87],"reasoning).":[88],"In":[89],"this":[90],"study,":[91],"current":[94],"attempts":[95],"combine":[97],"FCNs":[98],"we":[103],"fully":[104],"extracted":[105],"self-attention":[109],"by":[110],"designing":[111],"a":[112,121,153,164],"novel":[113],"attention":[114],"mechanism":[115],"3D":[117,144,154,165,178],"computation":[118,145],"new":[122,134],"framework":[124,135,170],"(named":[125],"3DTU)":[126],"three-dimensional":[128],"medical":[129],"image":[130],"tasks.":[132],"This":[133],"processes":[136],"images":[137],"an":[139],"end-to-end":[140],"manner":[141],"executes":[143],"on":[146,163,171],"both":[147],"encoder":[149],"side":[150,159],"(which":[151,160],"contains":[152],"transformer)":[155],"decoder":[158],"is":[161],"based":[162],"DCNN).":[166],"We":[167],"tested":[168],"our":[169,188],"two":[172],"independent":[173],"datasets":[174],"that":[175,187],"consist":[176],"MRI":[179],"CT":[181],"images.":[182],"Experimental":[183],"results":[184],"clearly":[185],"demonstrate":[186],"method":[189],"outperforms":[190],"state-of-the-art":[192],"methods":[194],"various":[196],"metrics.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":8}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}