{"id":"https://openalex.org/W4388726301","doi":"https://doi.org/10.1109/gcce59613.2023.10315552","title":"Automatic Detection of Focal Liver Lesions in Multi-phase CT Images Using One-Stage Object Detectors","display_name":"Automatic Detection of Focal Liver Lesions in Multi-phase CT Images Using One-Stage Object Detectors","publication_year":2023,"publication_date":"2023-10-10","ids":{"openalex":"https://openalex.org/W4388726301","doi":"https://doi.org/10.1109/gcce59613.2023.10315552"},"language":"en","primary_location":{"id":"doi:10.1109/gcce59613.2023.10315552","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce59613.2023.10315552","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 12th 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","School of Mathematical Sciences, Huaqiao University, Fujian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huaqiao University,School of Mathematical Sciences,Fujian,China","institution_ids":["https://openalex.org/I119045251"]},{"raw_affiliation_string":"School of Mathematical Sciences, Huaqiao University, 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","School of Mathematical Sciences, Huaqiao University, Fujian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huaqiao University,School of Mathematical Sciences,Fujian,China","institution_ids":["https://openalex.org/I119045251"]},{"raw_affiliation_string":"School of Mathematical Sciences, Huaqiao University, Fujian, China","institution_ids":["https://openalex.org/I119045251"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102580058","display_name":"ChangQiu 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":"ChangQiu Zhang","raw_affiliation_strings":["Huaqiao University,School of Mathematical Sciences,Fujian,China","School of Mathematical Sciences, Huaqiao University, Fujian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huaqiao University,School of Mathematical Sciences,Fujian,China","institution_ids":["https://openalex.org/I119045251"]},{"raw_affiliation_string":"School of Mathematical Sciences, Huaqiao University, 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/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":"Rahul Kumar Jain","raw_affiliation_strings":["Huaqiao University,School of Mathematical Sciences,Fujian,China","School of Mathematical Sciences, Huaqiao University, Fujian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huaqiao University,School of Mathematical Sciences,Fujian,China","institution_ids":["https://openalex.org/I119045251"]},{"raw_affiliation_string":"School of Mathematical Sciences, Huaqiao University, Fujian, China","institution_ids":["https://openalex.org/I119045251"]}]},{"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,Kusatsu,Japan","College of Information Science and Engineering, Ritsumeikan University, 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"]},{"raw_affiliation_string":"College of Information Science and Engineering, Ritsumeikan University, Kusatsu, 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":0.4386,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.68039903,"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":"712","last_page":"715"},"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":0.9987999796867371,"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":0.9987999796867371,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9966999888420105,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9934999942779541,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.6405879855155945},{"id":"https://openalex.org/keywords/stage","display_name":"Stage (stratigraphy)","score":0.6121312379837036},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5869892835617065},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5774250626564026},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5513883233070374},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4999842643737793},{"id":"https://openalex.org/keywords/phase","display_name":"Phase (matter)","score":0.46123194694519043},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.42655882239341736},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.255179762840271},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.25368982553482056},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1367644965648651}],"concepts":[{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.6405879855155945},{"id":"https://openalex.org/C146357865","wikidata":"https://www.wikidata.org/wiki/Q1123245","display_name":"Stage (stratigraphy)","level":2,"score":0.6121312379837036},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5869892835617065},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5774250626564026},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5513883233070374},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4999842643737793},{"id":"https://openalex.org/C44280652","wikidata":"https://www.wikidata.org/wiki/Q104837","display_name":"Phase (matter)","level":2,"score":0.46123194694519043},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.42655882239341736},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.255179762840271},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.25368982553482056},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1367644965648651},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/gcce59613.2023.10315552","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce59613.2023.10315552","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 12th 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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W2892351803","https://openalex.org/W3021753764","https://openalex.org/W3133737152","https://openalex.org/W4210955410","https://openalex.org/W4232632385","https://openalex.org/W4293584584","https://openalex.org/W4386076325","https://openalex.org/W6750227808","https://openalex.org/W6789980436"],"related_works":["https://openalex.org/W2366906938","https://openalex.org/W2349391998","https://openalex.org/W4205655149","https://openalex.org/W2503350049","https://openalex.org/W2329386257","https://openalex.org/W2000775715","https://openalex.org/W2397616145","https://openalex.org/W2795393339","https://openalex.org/W4390618967","https://openalex.org/W2626393719"],"abstract_inverted_index":{"Multi-phase":[0],"CT":[1,20,74,97,120],"images":[2,21],"are":[3],"widely":[4],"used":[5],"for":[6,39,148],"diagnosis":[7],"of":[8,14,57,89,96],"focal":[9,15,70,90],"liver":[10,16,71,91],"lesions.":[11],"Automatic":[12],"detection":[13,41,55,61,83,87],"lesions":[17,72,92],"in":[18,26,73],"multi-phase":[19],"is":[22,123,145],"an":[23],"essential":[24],"step":[25],"computer-aided":[27],"diagnosis.":[28],"In":[29,49],"recent":[30],"years,":[31],"many":[32],"deep":[33],"learning":[34],"methods":[35],"have":[36,44],"been":[37],"proposed":[38],"object":[40,60,136],"tasks":[42],"and":[43,66,107],"achieved":[45],"the":[46,54,79,114,119,128,134,142],"state-of-the-art":[47,139],"performance.":[48],"this":[50],"paper,":[51],"we":[52,116],"study":[53],"performance":[56,80,140],"using":[58],"one-stage":[59,135],"framework":[62],"(i.e.,":[63,99],"YOLOv3,":[64],"YOLOv5":[65],"YOLOv7)":[67],"to":[68,113,126],"detect":[69],"images.":[75],"We":[76,85],"also":[77],"compare":[78],"with":[81],"two-stage":[82],"frameworks.":[84],"analyze":[86],"accuracy":[88],"from":[93],"different":[94],"phases":[95],"scan":[98],"non-contract":[100],"enhanced":[101],"(NC)":[102],"phase,":[103,106],"arterial":[104],"(ART)":[105],"portal":[108],"venous":[109],"(PV)":[110],"phase).":[111],"According":[112],"analysis":[115],"can":[117],"determine":[118],"phase":[121,144],"which":[122],"best":[124],"suited":[125],"locate":[127],"lesion.":[129],"Experimental":[130],"results":[131],"show":[132],"that":[133],"detectors":[137],"achieve":[138],"while":[141],"PV":[143],"most":[146],"appropriate":[147],"lesion":[149],"detection.":[150]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
