{"id":"https://openalex.org/W7126035650","doi":"https://doi.org/10.1109/bibm66473.2025.11357148","title":"Dualmnet: a Lightweight Multi-Axis Interactive and Mask-Guided Network for Intracerebral Hemorrhage Segmentation","display_name":"Dualmnet: a Lightweight Multi-Axis Interactive and Mask-Guided Network for Intracerebral Hemorrhage Segmentation","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126035650","doi":"https://doi.org/10.1109/bibm66473.2025.11357148"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11357148","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11357148","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5124159285","display_name":"Jiayao Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I4610292","display_name":"Xiangtan University","ror":"https://ror.org/00xsfaz62","country_code":"CN","type":"education","lineage":["https://openalex.org/I4610292"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiayao Tang","raw_affiliation_strings":["Xiangtan University,Xiangtan,China"],"affiliations":[{"raw_affiliation_string":"Xiangtan University,Xiangtan,China","institution_ids":["https://openalex.org/I4610292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100368734","display_name":"Yuan Zhang","orcid":"https://orcid.org/0000-0002-8019-7944"},"institutions":[{"id":"https://openalex.org/I4610292","display_name":"Xiangtan University","ror":"https://ror.org/00xsfaz62","country_code":"CN","type":"education","lineage":["https://openalex.org/I4610292"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Zhang","raw_affiliation_strings":["Xiangtan University,Xiangtan,China"],"affiliations":[{"raw_affiliation_string":"Xiangtan University,Xiangtan,China","institution_ids":["https://openalex.org/I4610292"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xieping Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I173759888","display_name":"Hunan Normal University","ror":"https://ror.org/053w1zy07","country_code":"CN","type":"education","lineage":["https://openalex.org/I173759888"]},{"id":"https://openalex.org/I3130607311","display_name":"Changsha Normal University","ror":"https://ror.org/02sqk3z62","country_code":"CN","type":"education","lineage":["https://openalex.org/I3130607311"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xieping Gao","raw_affiliation_strings":["Hunan Normal University,Changsha,China"],"affiliations":[{"raw_affiliation_string":"Hunan Normal University,Changsha,China","institution_ids":["https://openalex.org/I3130607311","https://openalex.org/I173759888"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103012388","display_name":"Kai Hu","orcid":"https://orcid.org/0000-0003-1436-9522"},"institutions":[{"id":"https://openalex.org/I4610292","display_name":"Xiangtan University","ror":"https://ror.org/00xsfaz62","country_code":"CN","type":"education","lineage":["https://openalex.org/I4610292"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Hu","raw_affiliation_strings":["Xiangtan University,Xiangtan,China"],"affiliations":[{"raw_affiliation_string":"Xiangtan University,Xiangtan,China","institution_ids":["https://openalex.org/I4610292"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5124159285"],"corresponding_institution_ids":["https://openalex.org/I4610292"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.7125806,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2839","last_page":"2844"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11763","display_name":"Intracerebral and Subarachnoid Hemorrhage Research","score":0.9922000169754028,"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":0.9922000169754028,"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/T10227","display_name":"Acute Ischemic Stroke Management","score":0.0010999999940395355,"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/T11438","display_name":"Retinal Imaging and Analysis","score":0.000699999975040555,"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/segmentation","display_name":"Segmentation","score":0.8090999722480774},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6347000002861023},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5796999931335449},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.45249998569488525},{"id":"https://openalex.org/keywords/dice","display_name":"Dice","score":0.4489000141620636},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4180000126361847},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.3953999876976013},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3199000060558319}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8090999722480774},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7404000163078308},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6434999704360962},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6347000002861023},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5796999931335449},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.45249998569488525},{"id":"https://openalex.org/C22029948","wikidata":"https://www.wikidata.org/wiki/Q45089","display_name":"Dice","level":2,"score":0.4489000141620636},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43160000443458557},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4180000126361847},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.3953999876976013},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3199000060558319},{"id":"https://openalex.org/C2777094939","wikidata":"https://www.wikidata.org/wiki/Q1368943","display_name":"Intracerebral hemorrhage","level":3,"score":0.31139999628067017},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.30489999055862427},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.30149999260902405},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.29750001430511475},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.29159998893737793},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2648000121116638},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2637999951839447},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.2567000091075897}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11357148","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11357148","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8887965282","display_name":null,"funder_award_id":"62272404,62372170,62502419","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2583247392","https://openalex.org/W3004371585","https://openalex.org/W3041714909","https://openalex.org/W3118235341","https://openalex.org/W3119205652","https://openalex.org/W4226068227","https://openalex.org/W4295934721","https://openalex.org/W4386527666","https://openalex.org/W4387211614","https://openalex.org/W4387642391","https://openalex.org/W4387835477","https://openalex.org/W4388821320","https://openalex.org/W4396918399","https://openalex.org/W4400314340","https://openalex.org/W4401749301","https://openalex.org/W4402754250","https://openalex.org/W4403067122","https://openalex.org/W4408326352","https://openalex.org/W4410298150","https://openalex.org/W4415798491"],"related_works":[],"abstract_inverted_index":{"Intracerebral":[0],"hemorrhage":[1],"(ICH)":[2],"segmentation":[3,16,166],"is":[4],"a":[5,43,57,119],"critical":[6],"step":[7],"in":[8,165],"the":[9,73,90,109,133,142],"treatment":[10],"of":[11,76,92,113,136],"hemorrhagic":[12,102,147],"stroke.":[13],"Although":[14],"many":[15],"models":[17,164],"have":[18],"been":[19],"developed":[20],"for":[21,50],"this":[22,39],"task,":[23],"their":[24],"large":[25],"parameter":[26],"counts":[27],"and":[28,47,79,94,103,138,156],"high":[29],"computational":[30,85],"costs":[31],"hinder":[32],"deployment":[33],"on":[34,151],"mobile":[35],"devices.":[36],"To":[37],"address":[38],"challenge,":[40],"we":[41,117],"propose":[42],"lightweight":[44,163],"multi-axis":[45],"interactive":[46],"mask-guided":[48],"network":[49],"ICH":[51],"segmentation,":[52],"named":[53],"DualMNet.":[54],"DualMNet":[55,160],"integrates":[56],"Multi-Axis":[58],"Interactive":[59],"Attention":[60],"(MIA)":[61],"module,":[62],"which":[63],"utilizes":[64],"three-axis":[65],"interactions":[66],"to":[67,88,131,146],"generate":[68],"an":[69],"attention":[70],"map,":[71],"extracting":[72],"inherent":[74],"characteristics":[75],"CT":[77],"images":[78],"enhancing":[80],"feature":[81],"representation":[82],"with":[83],"minimal":[84],"cost.":[86],"Furthermore,":[87],"overcome":[89],"difficulties":[91],"missed":[93],"false":[95],"detections":[96],"caused":[97],"by":[98],"low":[99],"contrast":[100],"between":[101],"normal":[104],"tissues,":[105],"as":[106,108],"well":[107],"excessively":[110],"small":[111],"area":[112],"some":[114],"bleeding":[115],"regions,":[116],"design":[118],"Mask-Guided":[120],"Feature":[121],"Fusion":[122],"(MGFF)":[123],"module.":[124],"This":[125],"module":[126],"uses":[127],"intermediate":[128],"mask":[129],"predictions":[130],"guide":[132],"adaptive":[134],"fusion":[135],"low-level":[137],"high-level":[139],"features,":[140],"making":[141],"model":[143,175],"more":[144],"sensitive":[145],"regions.":[148],"Experimental":[149],"results":[150],"two":[152],"public":[153],"datasets,":[154],"PHY":[155],"BHSD,":[157],"demonstrate":[158],"that":[159],"outperforms":[161],"existing":[162],"accuracy,":[167],"achieving":[168],"higher":[169],"Dice":[170],"scores":[171],"while":[172],"significantly":[173],"reducing":[174],"parameters.":[176]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-01-30T00:00:00"}