{"id":"https://openalex.org/W2805378337","doi":"https://doi.org/10.1109/isbi.2018.8363516","title":"3D deep feature fusion in contrast-enhanced MR for malignancy characterization of hepatocellular carcinoma","display_name":"3D deep feature fusion in contrast-enhanced MR for malignancy characterization of hepatocellular carcinoma","publication_year":2018,"publication_date":"2018-04-01","ids":{"openalex":"https://openalex.org/W2805378337","doi":"https://doi.org/10.1109/isbi.2018.8363516","mag":"2805378337"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2018.8363516","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2018.8363516","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)","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/A5034226251","display_name":"Tianyou Dou","orcid":null},"institutions":[{"id":"https://openalex.org/I117532281","display_name":"Guangzhou University of Chinese Medicine","ror":"https://ror.org/03qb7bg95","country_code":"CN","type":"education","lineage":["https://openalex.org/I117532281"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tianyou Dou","raw_affiliation_strings":["School of Medical Information Engineering, Guangzhou University of Chinese Medicine, China"],"affiliations":[{"raw_affiliation_string":"School of Medical Information Engineering, Guangzhou University of Chinese Medicine, China","institution_ids":["https://openalex.org/I117532281"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100444064","display_name":"Lijuan Zhang","orcid":"https://orcid.org/0000-0003-0814-4925"},"institutions":[{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lijuan Zhang","raw_affiliation_strings":["Chinese Academy of Sciences, Shenzhen Institutes of Advanced Technology, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Shenzhen Institutes of Advanced Technology, Shenzhen, China","institution_ids":["https://openalex.org/I4210145761"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100606053","display_name":"Wu Zhou","orcid":"https://orcid.org/0000-0002-5917-1723"},"institutions":[{"id":"https://openalex.org/I117532281","display_name":"Guangzhou University of Chinese Medicine","ror":"https://ror.org/03qb7bg95","country_code":"CN","type":"education","lineage":["https://openalex.org/I117532281"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wu Zhou","raw_affiliation_strings":["School of Medical Information Engineering, Guangzhou University of Chinese Medicine, China"],"affiliations":[{"raw_affiliation_string":"School of Medical Information Engineering, Guangzhou University of Chinese Medicine, China","institution_ids":["https://openalex.org/I117532281"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5034226251"],"corresponding_institution_ids":["https://openalex.org/I117532281"],"apc_list":null,"apc_paid":null,"fwci":0.8841,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.74902121,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"29","last_page":"33"},"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":0.9998000264167786,"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":0.9998000264167786,"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/T10073","display_name":"Hepatocellular Carcinoma Treatment and Prognosis","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2721","display_name":"Hepatology"},"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/T11885","display_name":"MRI in cancer diagnosis","score":0.9955999851226807,"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/malignancy","display_name":"Malignancy","score":0.8622104525566101},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6585835218429565},{"id":"https://openalex.org/keywords/hepatocellular-carcinoma","display_name":"Hepatocellular carcinoma","score":0.5767654776573181},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.5516477823257446},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5300701856613159},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46886685490608215},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46687692403793335},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43509572744369507},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3535703420639038},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.33064132928848267},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.28383275866508484},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.20377621054649353},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.10731109976768494}],"concepts":[{"id":"https://openalex.org/C2779399171","wikidata":"https://www.wikidata.org/wiki/Q1483951","display_name":"Malignancy","level":2,"score":0.8622104525566101},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6585835218429565},{"id":"https://openalex.org/C2778019345","wikidata":"https://www.wikidata.org/wiki/Q1148337","display_name":"Hepatocellular carcinoma","level":2,"score":0.5767654776573181},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.5516477823257446},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5300701856613159},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46886685490608215},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46687692403793335},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43509572744369507},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3535703420639038},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.33064132928848267},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.28383275866508484},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.20377621054649353},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.10731109976768494},{"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:10.1109/isbi.2018.8363516","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2018.8363516","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.6399999856948853}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1972702908","https://openalex.org/W1990967415","https://openalex.org/W2054734446","https://openalex.org/W2095705004","https://openalex.org/W2126598020","https://openalex.org/W2156387975","https://openalex.org/W2160631108","https://openalex.org/W2163486683","https://openalex.org/W2163605009","https://openalex.org/W2343172899","https://openalex.org/W2345010043","https://openalex.org/W2530116934","https://openalex.org/W2592929672","https://openalex.org/W2639586488","https://openalex.org/W2793607670","https://openalex.org/W2919115771","https://openalex.org/W4211105405","https://openalex.org/W6674330103","https://openalex.org/W6682889407","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2417822880","https://openalex.org/W628600844","https://openalex.org/W1570838273","https://openalex.org/W2410885201","https://openalex.org/W2385390897","https://openalex.org/W3172842848","https://openalex.org/W2418745692","https://openalex.org/W2404951810","https://openalex.org/W2800415451","https://openalex.org/W2337719538"],"abstract_inverted_index":{"The":[0],"malignancy":[1,32,80,99,138,165,183,203],"of":[2,7,19,34,41,54,73,92,101,115,132,169,176],"hepatocellular":[3],"carcinoma":[4],"(HCC)":[5],"is":[6,192],"great":[8],"significance":[9],"to":[10,25,28,45,109],"prognosis.":[11],"Recently,":[12],"deep":[13,39,67,113,126,158,162,171,187],"feature":[14,40,68,114,127,159,163],"in":[15,58,76,95,189],"the":[16,51,55,71],"arterial":[17,62],"phase":[18,63,191,198,201],"Contrast-enhanced":[20,77,96,133,147,177],"MR":[21,78,97,134,148,178],"has":[22],"been":[23],"shown":[24],"be":[26,46],"superior":[27],"texture":[29],"features":[30,172,188],"for":[31,66,79,98,135,164,182,202],"characterization":[33,100],"HCCs.":[35],"However,":[36],"such":[37],"extracted":[38],"HCCs":[42,116],"was":[43,64],"limited":[44],"2D,":[47],"which":[48],"apparently":[49],"disregards":[50],"contextual":[52],"information":[53,87,94],"third":[56],"dimension":[57],"volumes.":[59],"Furthermore,":[60],"only":[61],"used":[65],"extraction,":[69],"ignoring":[70],"impact":[72],"other":[74],"phases":[75,131,175],"characterization.":[81,139,204],"To":[82],"further":[83],"enhance":[84],"volumetric":[85],"spatial":[86],"and":[88,199],"take":[89],"full":[90],"advantage":[91],"multi-phasic":[93],"HCC,":[102],"this":[103],"study":[104],"proposes":[105],"a":[106],"systematic":[107],"method":[108],"automatically":[110],"extract":[111],"3D":[112,119,157,170,186],"by":[117,125,195],"utilizing":[118],"convolution":[120],"neural":[121],"network":[122],"(CNN),":[123],"followed":[124,194],"fusion":[128,168],"from":[129,173],"multiple":[130,174],"more":[136],"accurate":[137],"Experimental":[140],"results":[141],"on":[142],"46":[143],"clinical":[144],"patients":[145],"with":[146],"images":[149],"show":[150],"several":[151],"intriguing":[152],"conclusions":[153],"as":[154],"follows:":[155],"(1)":[156],"outperforms":[160],"2D":[161],"characterization;":[166,184],"(2)":[167],"yields":[179],"better":[180],"performance":[181],"(3)":[185],"Arterial":[190],"best,":[193],"portal":[196],"vein":[197],"pre-contrast":[200]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}