{"id":"https://openalex.org/W4401750608","doi":"https://doi.org/10.1109/isbi56570.2024.10635400","title":"Bilateral Cross-Modal Fusion Network for Multimodal Whole-Body Tumor Segmentation","display_name":"Bilateral Cross-Modal Fusion Network for Multimodal Whole-Body Tumor Segmentation","publication_year":2024,"publication_date":"2024-05-27","ids":{"openalex":"https://openalex.org/W4401750608","doi":"https://doi.org/10.1109/isbi56570.2024.10635400"},"language":"en","primary_location":{"id":"doi:10.1109/isbi56570.2024.10635400","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/isbi56570.2024.10635400","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Symposium on Biomedical Imaging (ISBI)","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/A5115597138","display_name":"Tao Yu","orcid":"https://orcid.org/0009-0009-8017-9402"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tao Yu","raw_affiliation_strings":["Nanjing University of Science and Technology,School of Computer Science and Engineering,China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology,School of Computer Science and Engineering,China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037995294","display_name":"Xinrui Zhan","orcid":"https://orcid.org/0000-0001-9079-7401"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xinrui Zhan","raw_affiliation_strings":["Subtle Medical"],"affiliations":[{"raw_affiliation_string":"Subtle Medical","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045648457","display_name":"Lei Xiang","orcid":"https://orcid.org/0000-0002-0763-2313"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lei Xiang","raw_affiliation_strings":["Subtle Medical"],"affiliations":[{"raw_affiliation_string":"Subtle Medical","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103255400","display_name":"Xin Gao","orcid":"https://orcid.org/0000-0003-2444-8611"},"institutions":[{"id":"https://openalex.org/I4210089783","display_name":"Shanghai Medical Information Center","ror":"https://ror.org/007wz9933","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210089783"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Gao","raw_affiliation_strings":["Shanghai Universal Medical Imaging Diagnostic Center,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Universal Medical Imaging Diagnostic Center,Shanghai,China","institution_ids":["https://openalex.org/I4210089783"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061274720","display_name":"Tao Zhou","orcid":"https://orcid.org/0000-0002-2592-1688"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Zhou","raw_affiliation_strings":["Nanjing University of Science and Technology,School of Computer Science and Engineering,China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology,School of Computer Science and Engineering,China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5115597138"],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10944183,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10862","display_name":"AI in cancer detection","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.9991000294685364,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.6930253505706787},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5811285376548767},{"id":"https://openalex.org/keywords/multimodality","display_name":"Multimodality","score":0.5235640406608582},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5160667300224304},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5140582323074341},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4396052062511444},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32391393184661865},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.11279857158660889},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.05731761455535889}],"concepts":[{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.6930253505706787},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5811285376548767},{"id":"https://openalex.org/C2780910867","wikidata":"https://www.wikidata.org/wiki/Q1952416","display_name":"Multimodality","level":2,"score":0.5235640406608582},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5160667300224304},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5140582323074341},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4396052062511444},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32391393184661865},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.11279857158660889},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.05731761455535889},{"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},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi56570.2024.10635400","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/isbi56570.2024.10635400","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"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":22,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2898441006","https://openalex.org/W2979826702","https://openalex.org/W2998449272","https://openalex.org/W3014974815","https://openalex.org/W3108822985","https://openalex.org/W3112701542","https://openalex.org/W3203841574","https://openalex.org/W3215752673","https://openalex.org/W4210381648","https://openalex.org/W4212875960","https://openalex.org/W4220985875","https://openalex.org/W4221163766","https://openalex.org/W4295129660","https://openalex.org/W4296123084","https://openalex.org/W4296563087","https://openalex.org/W4309721374","https://openalex.org/W4311041597","https://openalex.org/W4320077478","https://openalex.org/W4367663280","https://openalex.org/W4396783545","https://openalex.org/W6843101575"],"related_works":["https://openalex.org/W4205899436","https://openalex.org/W2462138927","https://openalex.org/W3111427900","https://openalex.org/W4302009627","https://openalex.org/W4212781403","https://openalex.org/W4388989680","https://openalex.org/W2901011898","https://openalex.org/W3160379098","https://openalex.org/W2373442452","https://openalex.org/W2748609568"],"abstract_inverted_index":{"3D":[0,88],"whole-body":[1,89],"tumor":[2,90],"segmentation":[3,38,103],"plays":[4],"a":[5,26,79,108,131,149],"critical":[6],"role":[7],"in":[8,59,144],"cancer":[9],"treatment.":[10],"In":[11,74],"relation":[12],"to":[13,47,65,100,124,138,157],"this,":[14],"multimodal":[15,37,87,98,163],"fluorodeoxyglucose":[16],"(FDG)":[17],"positron":[18],"emission":[19],"tomography/computed":[20],"tomography":[21],"(PET/CT)":[22],"has":[23,62],"evolved":[24],"into":[25],"standard":[27],"imaging":[28],"procedure":[29],"for":[30,86,165],"the":[31,54,63,102,116,140,145,167],"evaluation":[32],"of":[33,56,97],"widespread":[34],"cancers.":[35],"Existing":[36],"methods":[39],"often":[40],"employ":[41],"spatial":[42],"and":[43,69,120],"channel":[44],"attention":[45,57],"mechanisms":[46,58],"fuse":[48],"features":[49,117,161],"from":[50,118,162],"different":[51],"modalities.":[52,129],"However,":[53],"incorporation":[55],"modal":[60],"fusion":[61],"potential":[64],"introduce":[66],"feature":[67,141],"interference":[68],"distort":[70],"detailed":[71],"image":[72],"features.":[73,169],"this":[75],"paper,":[76],"we":[77,106],"propose":[78,107],"novel":[80],"Bilateral":[81],"Cross-modal":[82],"Fusion":[83,111],"Network":[84],"(BCFNet)":[85],"segmentation,":[91],"which":[92],"can":[93],"effectively":[94],"make":[95],"use":[96],"information":[99,127],"improve":[101],"performance.":[104],"Specifically,":[105],"Multimodal":[109],"Enhancement":[110],"(MEF)":[112],"module":[113,154],"that":[114,173],"integrates":[115],"PET":[119],"CT":[121],"images,":[122],"aiming":[123],"capture":[125],"complementary":[126],"across":[128],"Additionally,":[130],"Local":[132],"Refinement":[133],"Module":[134,152],"(LRM)":[135],"is":[136,155],"presented":[137],"enhance":[139],"representations\u2019":[142],"ability":[143],"decoder":[146],"network.":[147],"Furthermore,":[148],"Feature":[150],"Aggregation":[151],"(FAM)":[153],"proposed":[156],"fully":[158],"integrate":[159],"previous":[160],"data":[164],"supplementing":[166],"output":[168],"Experimental":[170],"results":[171],"demonstrate":[172],"our":[174],"BCFNet":[175],"outperforms":[176],"other":[177],"comparison":[178],"methods.":[179]},"counts_by_year":[],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}