{"id":"https://openalex.org/W4327520743","doi":"https://doi.org/10.1145/3574198.3574206","title":"Classification of lymphoma subtypes in PET/CT images based on a bidirectional feature fusion method","display_name":"Classification of lymphoma subtypes in PET/CT images based on a bidirectional feature fusion method","publication_year":2022,"publication_date":"2022-11-10","ids":{"openalex":"https://openalex.org/W4327520743","doi":"https://doi.org/10.1145/3574198.3574206"},"language":"en","primary_location":{"id":"doi:10.1145/3574198.3574206","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1145/3574198.3574206","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 9th International Conference on Biomedical and Bioinformatics Engineering","raw_type":"proceedings-article"},"type":"conference-paper","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/A5103078270","display_name":"Wenbo Pang","orcid":"https://orcid.org/0000-0002-3641-8068"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenbo Pang","raw_affiliation_strings":["Department of Software College, Northeastern University, China"],"raw_orcid":"https://orcid.org/0000-0002-3641-8068","affiliations":[{"raw_affiliation_string":"Department of Software College, Northeastern University, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073727134","display_name":"Huiyan Jiang","orcid":"https://orcid.org/0000-0002-1428-8776"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huiyan Jiang","raw_affiliation_strings":["Department of Software College, Northeastern University, China"],"raw_orcid":"https://orcid.org/0000-0002-1428-8776","affiliations":[{"raw_affiliation_string":"Department of Software College, Northeastern University, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086420717","display_name":"Yonglong Zhang","orcid":"https://orcid.org/0000-0002-2356-842X"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yonglong Zhang","raw_affiliation_strings":["Department of Software College, Northeastern University, China"],"raw_orcid":"https://orcid.org/0000-0002-2356-842X","affiliations":[{"raw_affiliation_string":"Department of Software College, Northeastern University, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043274136","display_name":"Yizhou Chen","orcid":"https://orcid.org/0000-0001-7912-6447"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yizhou Chen","raw_affiliation_strings":["Department of Software College, Northeastern University, China"],"raw_orcid":"https://orcid.org/0000-0001-7912-6447","affiliations":[{"raw_affiliation_string":"Department of Software College, Northeastern University, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100430099","display_name":"Zhiguo Wang","orcid":"https://orcid.org/0000-0003-3686-6220"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhiguo Wang","raw_affiliation_strings":["Department of Nuclear Medicine, General Hospital of Northern Theater Command, China"],"raw_orcid":"https://orcid.org/0000-0003-3686-6220","affiliations":[{"raw_affiliation_string":"Department of Nuclear Medicine, General Hospital of Northern Theater Command, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101696423","display_name":"Jia Guo","orcid":"https://orcid.org/0000-0001-9333-7865"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jia Guo","raw_affiliation_strings":["Department of Nuclear Medicine, General Hospital of Northern Theater Command, China"],"raw_orcid":"https://orcid.org/0000-0001-9333-7865","affiliations":[{"raw_affiliation_string":"Department of Nuclear Medicine, General Hospital of Northern Theater Command, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060377398","display_name":"Guoxiu Lu","orcid":"https://orcid.org/0000-0001-5085-6163"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guoxiu Lu","raw_affiliation_strings":["Department of Nuclear Medicine, General Hospital of Northern Theater Command, China"],"raw_orcid":"https://orcid.org/0000-0001-5085-6163","affiliations":[{"raw_affiliation_string":"Department of Nuclear Medicine, General Hospital of Northern Theater Command, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101409130","display_name":"Youchao Wang","orcid":"https://orcid.org/0000-0003-2025-3139"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Youchao Wang","raw_affiliation_strings":["Department of Nuclear Medicine, General Hospital of Northern Theater Command, China"],"raw_orcid":"https://orcid.org/0000-0003-2025-3139","affiliations":[{"raw_affiliation_string":"Department of Nuclear Medicine, General Hospital of Northern Theater Command, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.30279528,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"49","last_page":"54"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9998999834060669,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9988999962806702,"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/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8246211409568787},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6807034611701965},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6592365503311157},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5549095273017883},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5486718416213989},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5425390005111694},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.542468249797821},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4946455657482147},{"id":"https://openalex.org/keywords/lymphoma","display_name":"Lymphoma","score":0.4921099543571472},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44878673553466797},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4140055179595947},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.13861316442489624},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.10760137438774109}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8246211409568787},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6807034611701965},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6592365503311157},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5549095273017883},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5486718416213989},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5425390005111694},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.542468249797821},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4946455657482147},{"id":"https://openalex.org/C2779338263","wikidata":"https://www.wikidata.org/wiki/Q208414","display_name":"Lymphoma","level":2,"score":0.4921099543571472},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44878673553466797},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4140055179595947},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.13861316442489624},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.10760137438774109},{"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:10.1145/3574198.3574206","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1145/3574198.3574206","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 9th International Conference on Biomedical and Bioinformatics Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.6299999952316284}],"awards":[{"id":"https://openalex.org/G2689429656","display_name":"\u57fa\u4e8ePET/CT\u5f71\u50cf\u7ec4\u5b66\u7684\u5168\u8eab\u6dcb\u5df4\u7624\u667a\u80fd\u8bca\u65ad\u5173\u952e\u6280\u672f\u7684\u7814\u7a76","funder_award_id":"61872075","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4622783489","display_name":null,"funder_award_id":"2021-YGJC-07","funder_id":"https://openalex.org/F4320323086","funder_display_name":"Natural Science Foundation of Liaoning Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323086","display_name":"Natural Science Foundation of Liaoning Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2136038762","https://openalex.org/W2153110463","https://openalex.org/W2194775991","https://openalex.org/W2809361304","https://openalex.org/W2883645764","https://openalex.org/W2982589596","https://openalex.org/W3002312636","https://openalex.org/W3021925134","https://openalex.org/W3086743023","https://openalex.org/W3092827891","https://openalex.org/W3101197104","https://openalex.org/W3115793789","https://openalex.org/W3119214506","https://openalex.org/W3119494456","https://openalex.org/W3121092655","https://openalex.org/W3160643432","https://openalex.org/W3206507930","https://openalex.org/W4200547735","https://openalex.org/W4224210955","https://openalex.org/W6768832384","https://openalex.org/W6770673972","https://openalex.org/W6774913070"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4313906399","https://openalex.org/W4321487865","https://openalex.org/W2811106690","https://openalex.org/W4239306820","https://openalex.org/W2947043951","https://openalex.org/W2318112981","https://openalex.org/W4312417841","https://openalex.org/W4225147082","https://openalex.org/W2778653980"],"abstract_inverted_index":{"Lymphoma":[0],"is":[1,31,174],"a":[2,87,94,143,172],"common":[3],"malignancy":[4],"that":[5,270],"endangers":[6],"human":[7],"life":[8],"and":[9,11,26,34,57,72,78,107,122,132,157,180,201,216,226,233,252,283],"health,":[10],"accurate":[12,27],"identification":[13],"of":[14,29,49,76,112,191,198,228,240,258],"lymphoma":[15,95,185,206,215,219,222,281],"from":[16],"PET/CT":[17,100,113,250],"images":[18,114],"has":[19,277],"great":[20],"value":[21],"in":[22,274],"clinical":[23],"treatment.":[24],"Efficient":[25],"discrimination":[28],"lymphomas":[30],"an":[32],"important":[33,43],"challenging":[35],"research":[36],"task.":[37],"However,":[38],"deep":[39,103,178],"networks":[40,121],"may":[41],"lose":[42],"features":[44,71,106,111,128,131,138,156,159],"such":[45],"as":[46],"texture":[47],"structure":[48],"the":[50,74,126,136,154,165,189,192,221,229,238,241,247,256,264,271],"target":[51],"while":[52],"acquiring":[53],"rich":[54],"image":[55],"information":[56],"even":[58],"misclassify":[59],"small-scale":[60],"targets.":[61],"Traditional":[62],"machine":[63,108,181],"learning":[64,104,109,179,182],"methods":[65,183],"rely":[66],"heavily":[67],"on":[68,118,150,164,220,246,280],"manually":[69],"designed":[70,195],"require":[73],"design":[75],"reasonable":[77],"effective":[79],"feature":[80,90,145,168],"combinations.":[81],"To":[82,187,236],"this":[83,275],"end,":[84],"we":[85,141,194,243],"propose":[86,142],"new":[88,144],"bidirectional":[89,167],"fusion":[91],"method":[92,148,273],"with":[93,263],"subtype":[96],"classification":[97,230,259,279],"model":[98,254],"for":[99,184],"images.":[101],"Firstly,":[102],"latent":[105,137,155],"explicit":[110,127,158],"are":[115,160],"extracted":[116],"based":[117,149,163],"convolutional":[119],"neural":[120],"prior":[123],"knowledge,":[124],"where":[125],"include":[129],"distribution":[130],"radiomics":[133],"features.":[134],"In":[135],"extraction":[139],"stage,":[140],"channel":[146],"compression":[147],"squeeze-and-excitation":[151],"normalization.":[152],"Then,":[153],"effectively":[161],"fused":[162],"proposed":[166,272],"selection":[169],"method.":[170],"Finally,":[171],"classifier":[173],"constructed":[175],"by":[176,260],"introducing":[177],"classification.":[186],"validate":[188,237],"effectiveness":[190],"model,":[193,242],"multiple":[196],"sets":[197],"comparison":[199],"experiments":[200,203,245,268],"ablation":[202],"to":[204,287],"classify":[205],"subtypes,":[207],"including":[208],"non-lymphoma,":[209],"Hodgkin's":[210],"lymphoma,":[211],"diffuse":[212],"large":[213],"B-cell":[214],"other":[217,288],"non-Hodgkin's":[218],"dataset.":[223],"The":[224,267],"accuracy":[225,257],"recall":[227],"reached":[231],"0.831":[232],"0.819,":[234],"respectively.":[235],"generalization":[239],"set":[244],"lung":[248],"cancer":[249],"dataset,":[251],"our":[253],"improved":[255],"0.045":[261],"compared":[262],"resnet18":[265],"network.":[266],"show":[269],"paper":[276],"better":[278],"dataset":[282],"can":[284],"be":[285],"applied":[286],"tumors.":[289]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}