{"id":"https://openalex.org/W3132884598","doi":"https://doi.org/10.1117/12.2582088","title":"Extremely imbalanced subarachnoid hemorrhage detection based on DenseNet-LSTM network with class-balanced loss and transfer learning","display_name":"Extremely imbalanced subarachnoid hemorrhage detection based on DenseNet-LSTM network with class-balanced loss and transfer learning","publication_year":2021,"publication_date":"2021-02-12","ids":{"openalex":"https://openalex.org/W3132884598","doi":"https://doi.org/10.1117/12.2582088","mag":"3132884598"},"language":"en","primary_location":{"id":"doi:10.1117/12.2582088","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2582088","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2021: Computer-Aided Diagnosis","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046786798","display_name":"Zhongyang Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Zhongyang Lu","raw_affiliation_strings":["Nagoya Univ. (Japan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nagoya Univ. (Japan)","institution_ids":["https://openalex.org/I60134161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074920808","display_name":"Masahiro Oda","orcid":"https://orcid.org/0000-0001-7714-422X"},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masahiro Oda","raw_affiliation_strings":["Nagoya Univ. (Japan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nagoya Univ. (Japan)","institution_ids":["https://openalex.org/I60134161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054846833","display_name":"Yuichiro Hayashi","orcid":"https://orcid.org/0000-0001-5241-8669"},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuichiro Hayashi","raw_affiliation_strings":["Nagoya Univ. (Japan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nagoya Univ. (Japan)","institution_ids":["https://openalex.org/I60134161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066091502","display_name":"Tao Hu","orcid":"https://orcid.org/0009-0002-6661-2723"},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tao Hu","raw_affiliation_strings":["Nagoya Univ. (Japan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nagoya Univ. (Japan)","institution_ids":["https://openalex.org/I60134161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086595860","display_name":"Hayato Itoh","orcid":"https://orcid.org/0000-0002-1410-1078"},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hayato Itoh","raw_affiliation_strings":["Nagoya Univ. (Japan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nagoya Univ. (Japan)","institution_ids":["https://openalex.org/I60134161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072478108","display_name":"Takeyuki Watadani","orcid":"https://orcid.org/0000-0002-3587-9356"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takeyuki Watadani","raw_affiliation_strings":["The Univ. of Tokyo (Japan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Univ. of Tokyo (Japan)","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021091713","display_name":"Osamu Abe","orcid":"https://orcid.org/0000-0002-1180-2629"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Osamu Abe","raw_affiliation_strings":["The Univ. of Tokyo (Japan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Univ. of Tokyo (Japan)","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016809176","display_name":"Masahiro Hashimoto","orcid":"https://orcid.org/0000-0003-0162-5312"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masahiro Hashimoto","raw_affiliation_strings":["Keio Univ. (Japan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Keio Univ. (Japan)","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078931094","display_name":"Masahiro Jinzaki","orcid":"https://orcid.org/0000-0002-8241-6565"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masahiro Jinzaki","raw_affiliation_strings":["Keio Univ. (Japan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Keio Univ. (Japan)","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032527419","display_name":"Kensaku Mori","orcid":"https://orcid.org/0000-0002-0100-4797"},"institutions":[{"id":"https://openalex.org/I184597095","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I184597095","https://openalex.org/I4210158934"]},{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kensaku Mori","raw_affiliation_strings":["Nagoya Univ. (Japan)","National Institute of Informatics (Japan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nagoya Univ. (Japan)","institution_ids":["https://openalex.org/I60134161"]},{"raw_affiliation_string":"National Institute of Informatics (Japan)","institution_ids":["https://openalex.org/I184597095"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":10,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1088,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.44636092,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"68","last_page":"68"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11763","display_name":"Intracerebral and Subarachnoid Hemorrhage Research","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/2728","display_name":"Neurology"},"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/T11763","display_name":"Intracerebral and Subarachnoid Hemorrhage Research","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/2728","display_name":"Neurology"},"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/T10706","display_name":"Traumatic Brain Injury and Neurovascular Disturbances","score":0.9905999898910522,"subfield":{"id":"https://openalex.org/subfields/2728","display_name":"Neurology"},"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/T10420","display_name":"Intracranial Aneurysms: Treatment and Complications","score":0.9887999892234802,"subfield":{"id":"https://openalex.org/subfields/2728","display_name":"Neurology"},"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/transfer-of-learning","display_name":"Transfer of learning","score":0.7143891453742981},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6462912559509277},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6327658295631409},{"id":"https://openalex.org/keywords/subarachnoid-hemorrhage","display_name":"Subarachnoid hemorrhage","score":0.6237898468971252},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5978488922119141},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5771548748016357},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5255528688430786},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.44893890619277954},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4450320303440094},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3890001177787781},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.23665112257003784},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2357153594493866},{"id":"https://openalex.org/keywords/surgery","display_name":"Surgery","score":0.16017621755599976}],"concepts":[{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.7143891453742981},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6462912559509277},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6327658295631409},{"id":"https://openalex.org/C2777736543","wikidata":"https://www.wikidata.org/wiki/Q693442","display_name":"Subarachnoid hemorrhage","level":2,"score":0.6237898468971252},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5978488922119141},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5771548748016357},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5255528688430786},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.44893890619277954},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4450320303440094},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3890001177787781},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.23665112257003784},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2357153594493866},{"id":"https://openalex.org/C141071460","wikidata":"https://www.wikidata.org/wiki/Q40821","display_name":"Surgery","level":1,"score":0.16017621755599976},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2582088","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2582088","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2021: Computer-Aided Diagnosis","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.49000000953674316,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4206357785","https://openalex.org/W3192840557","https://openalex.org/W4281381188","https://openalex.org/W2951211570","https://openalex.org/W3167935049","https://openalex.org/W3023427754","https://openalex.org/W4375928479","https://openalex.org/W3131673289","https://openalex.org/W3049131298","https://openalex.org/W3198847674"],"abstract_inverted_index":{"Subarachnoid":[0],"Hemorrhage":[1],"(SAH)":[2],"detection":[3,25,71,161],"is":[4],"a":[5,14,27,56,138,163],"critical,":[6],"severe":[7],"problem":[8,72],"that":[9],"confused":[10],"clinical":[11],"residents":[12],"for":[13],"long":[15],"time.":[16],"With":[17],"the":[18,35,63,69,80,83,92,97,111,127,156,166,181,185,188],"rise":[19],"of":[20,130,141,159],"deep":[21,44],"learning":[22,45,65,108],"technologies,":[23],"SAH":[24,70,122,160],"made":[26],"significant":[28],"breakthrough":[29],"in":[30],"recent":[31],"ten":[32],"years.":[33],"Whereas,":[34],"performances":[36],"are":[37,135],"significantly":[38],"degraded":[39],"on":[40,73,119,137,177],"imbalanced":[41,76],"data,":[42],"makes":[43],"models":[46],"have":[47],"always":[48],"suffered":[49],"criticism.":[50],"In":[51],"this":[52,178],"study,":[53],"we":[54],"present":[55],"DenseNet-LSTM":[57],"network":[58],"with":[59,151],"Class-Balanced":[60,104,182],"Loss":[61,183],"and":[62,93,106,114,147,176,184,194],"transfer":[64,107,174],"strategy":[66],"to":[67,79,109],"solve":[68],"an":[74,120],"extremely":[75],"dataset.":[77],"Compared":[78],"previous":[81],"works,":[82],"proposed":[84],"framework":[85],"not":[86],"merely":[87],"effectively":[88],"integrate":[89],"greyscale":[90],"features":[91],"spatial":[94],"information":[95],"from":[96],"consecutive":[98],"CT":[99],"scans,":[100],"but":[101],"also":[102],"employ":[103],"loss":[105],"alleviate":[110],"adverse":[112],"effects":[113],"broaden":[115],"feature":[116],"diversity":[117],"respectively":[118],"extreme":[121],"cases":[123,143,146,150],"scarcity":[124],"dataset,":[125,139],"mimicking":[126],"actual":[128],"situation":[129],"emergency":[131],"departments.":[132],"Comprehensive":[133],"experiments":[134],"conducted":[136],"consisted":[140],"2,519":[142],"without":[144],"hemorrhage":[145],"only":[148],"33":[149],"SAH.":[152],"Experimental":[153],"results":[154],"demonstrate":[155],"F-measure":[157,189],"score":[158,190],"achieved":[162],"remarkable":[164],"improvement,":[165],"backbone":[167],"DenseNet121":[168],"gained":[169],"around":[170],"33%":[171],"promotion":[172],"after":[173],"learning,":[175],"basis,":[179],"importing":[180],"LSTM":[186],"structure,":[187],"further":[191],"increased":[192],"6.1%":[193],"2.7%":[195],"sequentially.":[196]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}