{"id":"https://openalex.org/W3153846871","doi":"https://doi.org/10.3390/s21082675","title":"Semantic Cardiac Segmentation in Chest CT Images Using K-Means Clustering and the Mathematical Morphology Method","display_name":"Semantic Cardiac Segmentation in Chest CT Images Using K-Means Clustering and the Mathematical Morphology Method","publication_year":2021,"publication_date":"2021-04-10","ids":{"openalex":"https://openalex.org/W3153846871","doi":"https://doi.org/10.3390/s21082675","mag":"3153846871","pmid":"https://pubmed.ncbi.nlm.nih.gov/33920219"},"language":"en","primary_location":{"id":"doi:10.3390/s21082675","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21082675","pdf_url":"https://www.mdpi.com/1424-8220/21/8/2675/pdf?version=1618281872","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/21/8/2675/pdf?version=1618281872","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017604964","display_name":"Beanbonyka Rim","orcid":"https://orcid.org/0000-0003-1232-0610"},"institutions":[{"id":"https://openalex.org/I24541011","display_name":"Soonchunhyang University","ror":"https://ror.org/03qjsrb10","country_code":"KR","type":"education","lineage":["https://openalex.org/I24541011"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Beanbonyka Rim","raw_affiliation_strings":["Department of Software Convergence, Soonchunhyang University, Asan 31538, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Software Convergence, Soonchunhyang University, Asan 31538, Korea","institution_ids":["https://openalex.org/I24541011"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100720091","display_name":"Sung\u2010Jin Lee","orcid":"https://orcid.org/0000-0002-7865-7163"},"institutions":[{"id":"https://openalex.org/I24541011","display_name":"Soonchunhyang University","ror":"https://ror.org/03qjsrb10","country_code":"KR","type":"education","lineage":["https://openalex.org/I24541011"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sungjin Lee","raw_affiliation_strings":["Department of Software Convergence, Soonchunhyang University, Asan 31538, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Software Convergence, Soonchunhyang University, Asan 31538, Korea","institution_ids":["https://openalex.org/I24541011"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101748123","display_name":"Ahyoung Lee","orcid":"https://orcid.org/0000-0001-7467-3038"},"institutions":[{"id":"https://openalex.org/I172980758","display_name":"Kennesaw State University","ror":"https://ror.org/00jeqjx33","country_code":"US","type":"education","lineage":["https://openalex.org/I172980758"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ahyoung Lee","raw_affiliation_strings":["Department of Computer Science, Kennesaw State University, Marietta, GA 30144, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Kennesaw State University, Marietta, GA 30144, USA","institution_ids":["https://openalex.org/I172980758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025861169","display_name":"Hyo\u2010Wook Gil","orcid":"https://orcid.org/0000-0003-2550-2739"},"institutions":[{"id":"https://openalex.org/I24541011","display_name":"Soonchunhyang University","ror":"https://ror.org/03qjsrb10","country_code":"KR","type":"education","lineage":["https://openalex.org/I24541011"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyo-Wook Gil","raw_affiliation_strings":["Department of Internal Medicine, Soonchunhyang University Cheonan Hospital, Cheonan 31151, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Internal Medicine, Soonchunhyang University Cheonan Hospital, Cheonan 31151, Korea","institution_ids":["https://openalex.org/I24541011"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006130083","display_name":"Min Hong","orcid":"https://orcid.org/0000-0001-9963-5521"},"institutions":[{"id":"https://openalex.org/I24541011","display_name":"Soonchunhyang University","ror":"https://ror.org/03qjsrb10","country_code":"KR","type":"education","lineage":["https://openalex.org/I24541011"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Min Hong","raw_affiliation_strings":["Department of Computer Software Engineering, Soonchunhyang University, Asan 31538, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Software Engineering, Soonchunhyang University, Asan 31538, Korea","institution_ids":["https://openalex.org/I24541011"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5006130083"],"corresponding_institution_ids":["https://openalex.org/I24541011"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":1.3872,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.80509493,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"21","issue":"8","first_page":"2675","last_page":"2675"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9972000122070312,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9972000122070312,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9948999881744385,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9943000078201294,"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":0.7731812000274658},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.7164590954780579},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5823632478713989},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.5594717264175415},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.5412909388542175},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5382051467895508},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5230039954185486},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5000994205474854},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4917795956134796},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2564815878868103},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.12631288170814514},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07220175862312317}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7731812000274658},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.7164590954780579},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5823632478713989},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.5594717264175415},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.5412909388542175},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5382051467895508},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5230039954185486},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5000994205474854},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4917795956134796},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2564815878868103},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.12631288170814514},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07220175862312317},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012660","descriptor_name":"Semantics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012660","descriptor_name":"Semantics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012660","descriptor_name":"Semantics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":6,"locations":[{"id":"doi:10.3390/s21082675","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21082675","pdf_url":"https://www.mdpi.com/1424-8220/21/8/2675/pdf?version=1618281872","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:33920219","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33920219","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:digitalcommons.kennesaw.edu:facpubs-6157","is_oa":false,"landing_page_url":"https://digitalcommons.kennesaw.edu/facpubs/5001","pdf_url":null,"source":{"id":"https://openalex.org/S4377196456","display_name":"DigitalCommons - Kennesaw State University (Kennesaw State University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I172980758","host_organization_name":"Kennesaw State University","host_organization_lineage":["https://openalex.org/I172980758"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Faculty Articles","raw_type":"text"},{"id":"pmh:oai:doaj.org/article:8f4e323f29fd40d9a9dac8cb11d89992","is_oa":true,"landing_page_url":"https://doaj.org/article/8f4e323f29fd40d9a9dac8cb11d89992","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 21, Iss 8, p 2675 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/21/8/2675/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s21082675","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 21; Issue 8; Pages: 2675","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8070040","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8070040","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s21082675","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21082675","pdf_url":"https://www.mdpi.com/1424-8220/21/8/2675/pdf?version=1618281872","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6600000262260437,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3153846871.pdf","grobid_xml":"https://content.openalex.org/works/W3153846871.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1987971958","https://openalex.org/W1999478155","https://openalex.org/W2015159529","https://openalex.org/W2067191022","https://openalex.org/W2073459066","https://openalex.org/W2101234009","https://openalex.org/W2121947440","https://openalex.org/W2132068207","https://openalex.org/W2189580762","https://openalex.org/W2769848455","https://openalex.org/W2770180314","https://openalex.org/W2793788053","https://openalex.org/W2802527148","https://openalex.org/W2899743512","https://openalex.org/W2907274850","https://openalex.org/W2947263797","https://openalex.org/W2955609244","https://openalex.org/W2964184998","https://openalex.org/W2986869417","https://openalex.org/W3009563704","https://openalex.org/W3026497690","https://openalex.org/W3030186763","https://openalex.org/W3035665735","https://openalex.org/W3044707654","https://openalex.org/W3080830962","https://openalex.org/W3090609765","https://openalex.org/W3092263135","https://openalex.org/W3096243711","https://openalex.org/W3101612813","https://openalex.org/W3128670286","https://openalex.org/W6639824700","https://openalex.org/W6668990524","https://openalex.org/W6675354045","https://openalex.org/W6751152089","https://openalex.org/W6765077861","https://openalex.org/W6777483186","https://openalex.org/W6778200955","https://openalex.org/W6781049923"],"related_works":["https://openalex.org/W2953058328","https://openalex.org/W1542224353","https://openalex.org/W1661087619","https://openalex.org/W2750730210","https://openalex.org/W2116854923","https://openalex.org/W2236974868","https://openalex.org/W4312766348","https://openalex.org/W2730764323","https://openalex.org/W4233939244","https://openalex.org/W1997160662"],"abstract_inverted_index":{"Whole":[0],"cardiac":[1,39],"segmentation":[2,40,80],"in":[3,15,55,108],"chest":[4],"CT":[5],"images":[6,47],"is":[7,70],"important":[8],"to":[9,52],"identify":[10],"functional":[11],"abnormalities":[12],"that":[13],"occur":[14],"cardiovascular":[16],"diseases,":[17],"such":[18],"as":[19,64,84,96],"coronary":[20],"artery":[21],"disease":[22],"(CAD)":[23],"detection.":[24],"However,":[25],"manual":[26,44],"efforts":[27],"are":[28],"time-consuming":[29],"and":[30,60,92,120,168,176,192,196],"labor":[31],"intensive.":[32],"Additionally,":[33,155],"labeling":[34],"the":[35,42,49,53,57,61,89,130,136,142,150,156,180,183],"ground":[36],"truth":[37],"for":[38,182],"requires":[41],"extensive":[43],"annotation":[45],"of":[46,88,129,132,149,153,174,194],"by":[48],"radiologist.":[50],"Due":[51],"difficulty":[54],"obtaining":[56],"annotated":[58],"data":[59],"required":[62],"expertise":[63],"an":[65,67,145,164,190],"annotator,":[66],"unsupervised":[68],"approach":[69],"proposed.":[71],"In":[72,139],"this":[73],"paper,":[74],"we":[75],"introduce":[76],"a":[77,85,97],"semantic":[78],"whole-heart":[79],"combining":[81],"K-Means":[82,151],"clustering":[83],"threshold":[86,98],"criterion":[87],"mean-thresholding":[90],"method":[91,95,152],"mathematical":[93],"morphology":[94],"shifting":[99],"enhancer.":[100],"The":[101],"experiment":[102,157],"was":[103],"conducted":[104],"on":[105,158],"500":[106],"subjects":[107],"two":[109],"cases:":[110],"(1)":[111],"56":[112,159],"slices":[113,123,160,186],"per":[114,124,161,187],"volume":[115,125,162,188],"containing":[116,126],"full":[117],"heart":[118,133],"scans,":[119],"(2)":[121],"30":[122,185],"about":[127],"half":[128],"top":[131],"scans":[134],"before":[135],"liver":[137],"appears.":[138],"both":[140],"cases,":[141],"results":[143],"showed":[144],"average":[146],"silhouette":[147],"score":[148],"0.4130.":[154],"achieved":[163,189],"overall":[165],"accuracy":[166],"(OA)":[167],"mean":[169],"intersection":[170],"over":[171],"union":[172],"(mIoU)":[173],"34.90%":[175],"41.26%,":[177],"respectively,":[178],"while":[179],"performance":[181],"first":[184],"OA":[191],"mIoU":[193],"55.10%":[195],"71.46%,":[197],"respectively.":[198]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
