{"id":"https://openalex.org/W4322502569","doi":"https://doi.org/10.3390/s23052546","title":"Multi-Attention Segmentation Networks Combined with the Sobel Operator for Medical Images","display_name":"Multi-Attention Segmentation Networks Combined with the Sobel Operator for Medical Images","publication_year":2023,"publication_date":"2023-02-24","ids":{"openalex":"https://openalex.org/W4322502569","doi":"https://doi.org/10.3390/s23052546","pmid":"https://pubmed.ncbi.nlm.nih.gov/36904754"},"language":"en","primary_location":{"id":"doi:10.3390/s23052546","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23052546","pdf_url":"https://www.mdpi.com/1424-8220/23/5/2546/pdf?version=1677249648","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/1424-8220/23/5/2546/pdf?version=1677249648","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043426199","display_name":"Fangfang Lu","orcid":"https://orcid.org/0000-0001-8228-5422"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]},{"id":"https://openalex.org/I23632641","display_name":"Shanghai University of Electric Power","ror":"https://ror.org/02w4tny03","country_code":"CN","type":"education","lineage":["https://openalex.org/I23632641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fangfang Lu","raw_affiliation_strings":["College of Computer Science and Technology, Shanghai University of Electric Power, Shanghai 201399, China","Department of Electronic Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China"],"raw_orcid":"https://orcid.org/0000-0001-8228-5422","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Shanghai University of Electric Power, Shanghai 201399, China","institution_ids":["https://openalex.org/I23632641"]},{"raw_affiliation_string":"Department of Electronic Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037142989","display_name":"Chi Tang","orcid":"https://orcid.org/0000-0001-9673-5906"},"institutions":[{"id":"https://openalex.org/I23632641","display_name":"Shanghai University of Electric Power","ror":"https://ror.org/02w4tny03","country_code":"CN","type":"education","lineage":["https://openalex.org/I23632641"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chi Tang","raw_affiliation_strings":["College of Computer Science and Technology, Shanghai University of Electric Power, Shanghai 201399, China"],"raw_orcid":"https://orcid.org/0000-0001-9673-5906","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Shanghai University of Electric Power, Shanghai 201399, China","institution_ids":["https://openalex.org/I23632641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101732797","display_name":"Tianxiang Liu","orcid":"https://orcid.org/0000-0001-6848-0424"},"institutions":[{"id":"https://openalex.org/I23632641","display_name":"Shanghai University of Electric Power","ror":"https://ror.org/02w4tny03","country_code":"CN","type":"education","lineage":["https://openalex.org/I23632641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianxiang Liu","raw_affiliation_strings":["College of Computer Science and Technology, Shanghai University of Electric Power, Shanghai 201399, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Shanghai University of Electric Power, Shanghai 201399, China","institution_ids":["https://openalex.org/I23632641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100361538","display_name":"Zhihao Zhang","orcid":"https://orcid.org/0000-0002-6936-3999"},"institutions":[{"id":"https://openalex.org/I23632641","display_name":"Shanghai University of Electric Power","ror":"https://ror.org/02w4tny03","country_code":"CN","type":"education","lineage":["https://openalex.org/I23632641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihao Zhang","raw_affiliation_strings":["College of Computer Science and Technology, Shanghai University of Electric Power, Shanghai 201399, China"],"raw_orcid":"https://orcid.org/0000-0002-6936-3999","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Shanghai University of Electric Power, Shanghai 201399, China","institution_ids":["https://openalex.org/I23632641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033615240","display_name":"Leida Li","orcid":"https://orcid.org/0000-0001-9069-8796"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Leida Li","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi\u2019an 710000, China","School of Artificial Intelligence, Xidian University, Xi'an 710000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi\u2019an 710000, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an 710000, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5037142989"],"corresponding_institution_ids":["https://openalex.org/I23632641"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":4.6549,"has_fulltext":true,"cited_by_count":30,"citation_normalized_percentile":{"value":0.95864226,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"23","issue":"5","first_page":"2546","last_page":"2546"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9998999834060669,"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":0.9998999834060669,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9950000047683716,"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/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9783999919891357,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/sobel-operator","display_name":"Sobel operator","score":0.836548924446106},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7732588052749634},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7343316674232483},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.682451605796814},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5900208950042725},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4928865432739258},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4608660638332367},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44482171535491943},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.32739776372909546},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.279479056596756},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2010241448879242}],"concepts":[{"id":"https://openalex.org/C30703548","wikidata":"https://www.wikidata.org/wiki/Q1757673","display_name":"Sobel operator","level":5,"score":0.836548924446106},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7732588052749634},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7343316674232483},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.682451605796814},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5900208950042725},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4928865432739258},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4608660638332367},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44482171535491943},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.32739776372909546},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.279479056596756},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2010241448879242},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","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":"D007743","descriptor_name":"Labor, Obstetric","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007743","descriptor_name":"Labor, Obstetric","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007743","descriptor_name":"Labor, Obstetric","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011247","descriptor_name":"Pregnancy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011247","descriptor_name":"Pregnancy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011247","descriptor_name":"Pregnancy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":5,"locations":[{"id":"doi:10.3390/s23052546","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23052546","pdf_url":"https://www.mdpi.com/1424-8220/23/5/2546/pdf?version=1677249648","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:36904754","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36904754","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:pubmedcentral.nih.gov:10007317","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10007317","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10007317/pdf/sensors-23-02546.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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"},{"id":"pmh:oai:doaj.org/article:57c09383e8774b199676c377739a461e","is_oa":true,"landing_page_url":"https://doaj.org/article/57c09383e8774b199676c377739a461e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"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 23, Iss 5, p 2546 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/23/5/2546/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s23052546","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","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s23052546","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23052546","pdf_url":"https://www.mdpi.com/1424-8220/23/5/2546/pdf?version=1677249648","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":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4322502569.pdf"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2581772000","https://openalex.org/W2905103531","https://openalex.org/W2911605501","https://openalex.org/W2925924778","https://openalex.org/W2953881420","https://openalex.org/W2955058313","https://openalex.org/W2962767316","https://openalex.org/W2963881378","https://openalex.org/W2964309882","https://openalex.org/W2997866913","https://openalex.org/W2997876626","https://openalex.org/W3007497549","https://openalex.org/W3008985036","https://openalex.org/W3014725478","https://openalex.org/W3019980738","https://openalex.org/W3027763298","https://openalex.org/W3032510608","https://openalex.org/W3048223502","https://openalex.org/W3068494733","https://openalex.org/W3096956107","https://openalex.org/W3102469298","https://openalex.org/W3104810384","https://openalex.org/W3108591672","https://openalex.org/W3112175976","https://openalex.org/W3115781494","https://openalex.org/W3122784054","https://openalex.org/W3127323183","https://openalex.org/W3128131898","https://openalex.org/W3135352607","https://openalex.org/W3164607782","https://openalex.org/W3169865585","https://openalex.org/W3184641956","https://openalex.org/W4200462422","https://openalex.org/W4220771488","https://openalex.org/W4220860377","https://openalex.org/W4225271274","https://openalex.org/W4226301203","https://openalex.org/W4229062308","https://openalex.org/W4283014995","https://openalex.org/W4294975383","https://openalex.org/W6770858627","https://openalex.org/W6784557086","https://openalex.org/W6788885258","https://openalex.org/W6791471809","https://openalex.org/W6800186178"],"related_works":["https://openalex.org/W4388400392","https://openalex.org/W2383455043","https://openalex.org/W1974517722","https://openalex.org/W2367735169","https://openalex.org/W2269083758","https://openalex.org/W4225576506","https://openalex.org/W2545393398","https://openalex.org/W2378692644","https://openalex.org/W2412868618","https://openalex.org/W3212250818"],"abstract_inverted_index":{"Medical":[0],"images":[1,14,33],"are":[2,15,176,182],"used":[3,51],"as":[4,17],"an":[5,18,96],"important":[6,19],"basis":[7],"for":[8,21,52,87,144,148],"diagnosing":[9,22],"diseases,":[10],"among":[11],"which":[12,181],"CT":[13,32,58],"seen":[16],"tool":[20],"lung":[23,76],"lesions.":[24,150],"However,":[25,60],"manual":[26],"segmentation":[27,55,62,90,146,189],"of":[28,56,64,75,171],"infected":[29],"areas":[30],"in":[31,186],"is":[34,67,142],"time-consuming":[35],"and":[36,130,165,178],"laborious.":[37],"With":[38],"its":[39],"excellent":[40],"feature":[41,98],"extraction":[42],"capabilities,":[43],"a":[44,80,125,131],"deep":[45],"learning-based":[46],"method":[47],"has":[48],"been":[49],"widely":[50],"automatic":[53],"lesion":[54,89],"COVID-19":[57,88,154],"images.":[59],"the":[61,73,102,111,116,138,145,159,172],"accuracy":[63],"these":[65],"methods":[66],"still":[68],"limited.":[69],"To":[70,114],"effectively":[71],"quantify":[72],"severity":[74],"infections,":[77],"we":[78],"propose":[79],"Sobel":[81,103],"operator":[82,104],"combined":[83],"with":[84],"multi-attention":[85],"networks":[86],"(SMA-Net).":[91],"In":[92,136],"our":[93],"SMA-Net":[94,123,174],"method,":[95],"edge":[97,107],"fusion":[99],"module":[100],"uses":[101],"to":[105,110,118],"add":[106],"detail":[108],"information":[109],"input":[112],"image.":[113],"guide":[115],"network":[117,147],"focus":[119],"on":[120,153],"key":[121],"regions,":[122],"introduces":[124],"self-attentive":[126],"channel":[127],"attention":[128,134],"mechanism":[129],"spatial":[132],"linear":[133],"mechanism.":[135],"addition,":[137],"Tversky":[139],"loss":[140],"function":[141],"adopted":[143],"small":[149],"Comparative":[151],"experiments":[152],"public":[155],"datasets":[156],"show":[157],"that":[158],"average":[160],"Dice":[161],"similarity":[162],"coefficient":[163],"(DSC)":[164],"joint":[166],"intersection":[167],"over":[168],"union":[169],"(IOU)":[170],"proposed":[173],"model":[175],"86.1%":[177],"77.8%,":[179],"respectively,":[180],"better":[183],"than":[184],"those":[185],"most":[187],"existing":[188],"networks.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":4}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}
