{"id":"https://openalex.org/W7126049396","doi":"https://doi.org/10.1109/acompa69200.2025.00014","title":"Efficient Hybrid Architecture of U-Net and VGG for Liver Cancer Diagnosis","display_name":"Efficient Hybrid Architecture of U-Net and VGG for Liver Cancer Diagnosis","publication_year":2025,"publication_date":"2025-11-27","ids":{"openalex":"https://openalex.org/W7126049396","doi":"https://doi.org/10.1109/acompa69200.2025.00014"},"language":null,"primary_location":{"id":"doi:10.1109/acompa69200.2025.00014","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acompa69200.2025.00014","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 19th International Conference on Advanced Computing and Analytics (ACOMPA)","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/A5048247702","display_name":"L\u00e2m Tu\u1ea5n Ki\u1ec7t","orcid":null},"institutions":[{"id":"https://openalex.org/I123565023","display_name":"Vietnam National University Ho Chi Minh City","ror":"https://ror.org/00waaqh38","country_code":"VN","type":"education","lineage":["https://openalex.org/I123565023"]}],"countries":["VN"],"is_corresponding":true,"raw_author_name":"Lam Tuan Kiet","raw_affiliation_strings":["University of Information Technology Vietnam National University,Faculty of Information Science and Engineering,Ho Chi Minh City,Vietnam"],"affiliations":[{"raw_affiliation_string":"University of Information Technology Vietnam National University,Faculty of Information Science and Engineering,Ho Chi Minh City,Vietnam","institution_ids":["https://openalex.org/I123565023"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056726536","display_name":"Ha Minh Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I123565023","display_name":"Vietnam National University Ho Chi Minh City","ror":"https://ror.org/00waaqh38","country_code":"VN","type":"education","lineage":["https://openalex.org/I123565023"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Ha Minh Tan","raw_affiliation_strings":["University of Information Technology Vietnam National University,Faculty of Information Science and Engineering,Ho Chi Minh City,Vietnam"],"affiliations":[{"raw_affiliation_string":"University of Information Technology Vietnam National University,Faculty of Information Science and Engineering,Ho Chi Minh City,Vietnam","institution_ids":["https://openalex.org/I123565023"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5048247702"],"corresponding_institution_ids":["https://openalex.org/I123565023"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.73380412,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"42","last_page":"49"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.7013000249862671,"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":0.7013000249862671,"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/T10862","display_name":"AI in cancer detection","score":0.13950000703334808,"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/T11438","display_name":"Retinal Imaging and Analysis","score":0.02239999920129776,"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":0.7186999917030334},{"id":"https://openalex.org/keywords/dice","display_name":"Dice","score":0.6571000218391418},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.569100022315979},{"id":"https://openalex.org/keywords/liver-cancer","display_name":"Liver cancer","score":0.5012000203132629},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4851999878883362},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4625000059604645},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4187999963760376},{"id":"https://openalex.org/keywords/s\u00f8rensen\u2013dice-coefficient","display_name":"S\u00f8rensen\u2013Dice coefficient","score":0.3955000042915344}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7186999917030334},{"id":"https://openalex.org/C22029948","wikidata":"https://www.wikidata.org/wiki/Q45089","display_name":"Dice","level":2,"score":0.6571000218391418},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6019999980926514},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5958999991416931},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.569100022315979},{"id":"https://openalex.org/C2776231280","wikidata":"https://www.wikidata.org/wiki/Q623031","display_name":"Liver cancer","level":3,"score":0.5012000203132629},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4851999878883362},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4625000059604645},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4187999963760376},{"id":"https://openalex.org/C163892561","wikidata":"https://www.wikidata.org/wiki/Q2613728","display_name":"S\u00f8rensen\u2013Dice coefficient","level":4,"score":0.3955000042915344},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3880999982357025},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.3668999969959259},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.3361000120639801},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.31220000982284546},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3107999861240387},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2913999855518341},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.2757999897003174},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.27300000190734863},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.271699994802475},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.25519999861717224}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acompa69200.2025.00014","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acompa69200.2025.00014","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 19th International Conference on Advanced Computing and Analytics (ACOMPA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.5121196508407593,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2417429787","https://openalex.org/W2463818697","https://openalex.org/W2464708700","https://openalex.org/W2526009326","https://openalex.org/W2592929672","https://openalex.org/W2884436604","https://openalex.org/W2910094941","https://openalex.org/W2919115771","https://openalex.org/W2962914239","https://openalex.org/W2963163009","https://openalex.org/W2963446712","https://openalex.org/W2964227007","https://openalex.org/W2982083293","https://openalex.org/W3014713533","https://openalex.org/W3014974815","https://openalex.org/W3131151690","https://openalex.org/W3177452764","https://openalex.org/W3187589338","https://openalex.org/W4210629573","https://openalex.org/W4283806161","https://openalex.org/W4290466595","https://openalex.org/W4291149557","https://openalex.org/W4296500922","https://openalex.org/W4388293201","https://openalex.org/W4392013639","https://openalex.org/W4393217456","https://openalex.org/W4400084034","https://openalex.org/W4411379354"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"liver":[1,33,87,141],"cancer":[2,34,142],"diagnosis":[3,143],"is":[4,50],"critical":[5],"for":[6,42,140],"early":[7],"intervention":[8],"and":[9,25,36,47,89,117,135],"improved":[10,90],"patient":[11],"outcomes.":[12],"This":[13,68,121],"paper":[14],"proposes":[15],"a":[16,58,137],"novel":[17],"framework":[18],"that":[19],"bridges":[20],"the":[21,54,72,78,95,113,124],"strengths":[22],"of":[23,75,81,86,126],"U-Net":[24,39,76],"VGG":[26,55],"architectures":[27],"to":[28,61],"achieve":[29],"superior":[30],"performance":[31],"in":[32,108,130,144],"segmentation":[35,85,109],"diagnosis.":[37],"The":[38],"model,":[40],"known":[41],"its":[43,63],"robust":[44],"feature":[45,59],"extraction":[46],"localization":[48],"capabilities,":[49],"enhanced":[51],"by":[52],"integrating":[53],"network":[56],"as":[57,112],"encoder":[60],"leverage":[62],"pre-trained":[64],"deep":[65],"hierarchical":[66],"features.":[67],"hybrid":[69,100],"approach":[70],"combines":[71],"spatial":[73],"accuracy":[74],"with":[77,105],"representational":[79],"power":[80],"VGG,":[82],"enabling":[83],"precise":[84],"tumors":[88],"diagnostic":[91],"accuracy.":[92],"Evaluated":[93],"on":[94],"LiTS":[96],"dataset,":[97],"our":[98],"efficient":[99],"model":[101],"demonstrates":[102],"state-of-the-art":[103],"performance,":[104],"significant":[106],"improvements":[107],"metrics":[110],"such":[111],"Dice":[114],"Similarity":[115],"Coefficient":[116],"Intersection":[118],"over":[119],"Union.":[120],"work":[122],"highlights":[123],"potential":[125],"synergistic":[127],"architectural":[128],"design":[129],"advancing":[131],"medical":[132],"image":[133],"analysis":[134],"offers":[136],"scalable":[138],"solution":[139],"clinical":[145],"settings.":[146]},"counts_by_year":[],"updated_date":"2026-02-23T20:09:44.859080","created_date":"2026-01-30T00:00:00"}