{"id":"https://openalex.org/W4406265898","doi":"https://doi.org/10.1109/gcce62371.2024.10761031","title":"Detection of Focal Liver Lesions in CT Images Using a Transformer-Based End-to-End Detection Model","display_name":"Detection of Focal Liver Lesions in CT Images Using a Transformer-Based End-to-End Detection Model","publication_year":2024,"publication_date":"2024-10-29","ids":{"openalex":"https://openalex.org/W4406265898","doi":"https://doi.org/10.1109/gcce62371.2024.10761031"},"language":"en","primary_location":{"id":"doi:10.1109/gcce62371.2024.10761031","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce62371.2024.10761031","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 13th Global Conference on Consumer Electronics (GCCE)","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/A5070170275","display_name":"Jian Song","orcid":"https://orcid.org/0000-0001-9957-6533"},"institutions":[{"id":"https://openalex.org/I119045251","display_name":"Huaqiao University","ror":"https://ror.org/03frdh605","country_code":"CN","type":"education","lineage":["https://openalex.org/I119045251"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Song","raw_affiliation_strings":["Huaqiao University,School of Mathematical Sciences,Fujian,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huaqiao University,School of Mathematical Sciences,Fujian,China","institution_ids":["https://openalex.org/I119045251"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101655895","display_name":"Yan Hu","orcid":"https://orcid.org/0000-0003-4878-5364"},"institutions":[{"id":"https://openalex.org/I119045251","display_name":"Huaqiao University","ror":"https://ror.org/03frdh605","country_code":"CN","type":"education","lineage":["https://openalex.org/I119045251"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"YuChang Hu","raw_affiliation_strings":["Huaqiao University,School of Mathematical Sciences,Fujian,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huaqiao University,School of Mathematical Sciences,Fujian,China","institution_ids":["https://openalex.org/I119045251"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063008808","display_name":"JunHao Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I119045251","display_name":"Huaqiao University","ror":"https://ror.org/03frdh605","country_code":"CN","type":"education","lineage":["https://openalex.org/I119045251"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"JunHao Zhang","raw_affiliation_strings":["Huaqiao University,School of Mathematical Sciences,Fujian,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huaqiao University,School of Mathematical Sciences,Fujian,China","institution_ids":["https://openalex.org/I119045251"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089542345","display_name":"Rahul Kumar Jain","orcid":"https://orcid.org/0000-0002-0768-2193"},"institutions":[{"id":"https://openalex.org/I135768898","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03","country_code":"JP","type":"education","lineage":["https://openalex.org/I135768898","https://openalex.org/I4390039241"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Rahul Jain","raw_affiliation_strings":["Ritsumeikan University,College of Information Science and Engineering,Kusatsu,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ritsumeikan University,College of Information Science and Engineering,Kusatsu,Japan","institution_ids":["https://openalex.org/I135768898"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044216245","display_name":"Yen\u2010Wei Chen","orcid":"https://orcid.org/0000-0002-5952-0188"},"institutions":[{"id":"https://openalex.org/I135768898","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03","country_code":"JP","type":"education","lineage":["https://openalex.org/I135768898","https://openalex.org/I4390039241"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yen-Wei Chen","raw_affiliation_strings":["Ritsumeikan University,College of Information Science and Engineering,Osaka,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ritsumeikan University,College of Information Science and Engineering,Osaka,Japan","institution_ids":["https://openalex.org/I135768898"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3256,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.56778731,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1061","last_page":"1064"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9613999724388123,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9613999724388123,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9592000246047974,"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"}},{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9041000008583069,"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/end-to-end-principle","display_name":"End-to-end principle","score":0.5699807405471802},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47991952300071716},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.46016404032707214},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3906497359275818},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3794138729572296},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.3477475643157959},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2290453016757965},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.181924968957901},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.0765780508518219},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.060124605894088745}],"concepts":[{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.5699807405471802},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47991952300071716},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.46016404032707214},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3906497359275818},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3794138729572296},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.3477475643157959},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2290453016757965},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.181924968957901},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0765780508518219},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.060124605894088745}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/gcce62371.2024.10761031","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce62371.2024.10761031","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 13th Global Conference on Consumer Electronics (GCCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320316884","display_name":"Natural Science Foundation of Xiamen City","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Automatic":[0],"detection":[1,26,42,69,75,134],"of":[2,16,141],"focal":[3,81,144],"liver":[4,17,40,82],"lesions":[5,83],"in":[6,13,84,132],"CT":[7,85],"image":[8,123],"is":[9],"an":[10],"essential":[11],"step":[12],"computer-aided":[14],"diagnosis":[15],"cancers.":[18],"Several":[19],"convolutional":[20],"neural":[21],"network":[22],"(CNN)":[23],"based":[24],"object":[25,129],"methods":[27,92],"(i.e.,":[28,77,125],"Faster":[29,94],"R-CNN,":[30],"YOLO,":[31],"center":[32],"Net":[33],"et.":[34],"al.)":[35],"have":[36],"been":[37],"proposed":[38],"for":[39,60,79,100,128,143],"lesion":[41,145],"and":[43,56,87,96],"achieved":[44],"the":[45,68,117,121,139],"state-of-the-art":[46],"results.":[47],"But":[48],"these":[49],"CNN-based":[50],"models":[51],"use":[52],"predefined":[53],"anchor":[54,108],"boxes":[55],"requires":[57],"manual":[58],"adjustments":[59],"different":[61],"datasets.":[62],"In":[63],"this":[64],"paper,":[65],"we":[66],"study":[67],"performance":[70],"using":[71,93],"a":[72],"transformer-based":[73],"end-to-end":[74,101],"model":[76,118],"DETR)":[78],"detecting":[80],"images":[86],"compare":[88],"them":[89],"with":[90],"existing":[91],"R-CNN":[95],"YOLO.":[97],"DETR":[98,111,142],"allows":[99],"learning":[102],"without":[103],"requiring":[104],"hand-designed":[105],"components":[106],"like":[107],"boxes.":[109],"Additionally,":[110],"uses":[112],"self-attention":[113],"mechanisms":[114],"that":[115],"enable":[116],"to":[119],"consider":[120],"entire":[122],"context":[124],"global":[126],"context)":[127],"detection,":[130],"resulting":[131],"high":[133],"accuracy.":[135],"Experimental":[136],"results":[137],"demonstrate":[138],"effectiveness":[140],"detection.":[146]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
