{"id":"https://openalex.org/W3185105934","doi":"https://doi.org/10.1145/3446618","title":"A Densely Connected Network Based on U-Net for Medical Image Segmentation","display_name":"A Densely Connected Network Based on U-Net for Medical Image Segmentation","publication_year":2021,"publication_date":"2021-07-22","ids":{"openalex":"https://openalex.org/W3185105934","doi":"https://doi.org/10.1145/3446618","mag":"3185105934"},"language":"en","primary_location":{"id":"doi:10.1145/3446618","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3446618","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","raw_type":"journal-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/A5086862160","display_name":"Zhenzhen Yang","orcid":"https://orcid.org/0000-0002-5763-2768"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenzhen Yang","raw_affiliation_strings":["Nanjing University of Posts and Telecommunications, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100600605","display_name":"Pengfei Xu","orcid":"https://orcid.org/0000-0002-7304-734X"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengfei Xu","raw_affiliation_strings":["Nanjing University of Posts and Telecommunications, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064679236","display_name":"Yongpeng Yang","orcid":"https://orcid.org/0000-0003-3992-2814"},"institutions":[{"id":"https://openalex.org/I4210164796","display_name":"Nanjing Polytechnic Institute","ror":"https://ror.org/05tt6m403","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210164796"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongpeng Yang","raw_affiliation_strings":["Nanjing Vocational College of Information Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing Vocational College of Information Technology, China","institution_ids":["https://openalex.org/I4210164796"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007962086","display_name":"Bing\u2010Kun Bao","orcid":"https://orcid.org/0000-0001-5956-831X"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bing-Kun Bao","raw_affiliation_strings":["Nanjing University of Posts and Telecommunications, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I41198531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.6381,"has_fulltext":false,"cited_by_count":41,"citation_normalized_percentile":{"value":0.91653522,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"17","issue":"3","first_page":"1","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9990000128746033,"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/T10862","display_name":"AI in cancer detection","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8263691663742065},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.739124059677124},{"id":"https://openalex.org/keywords/cross-entropy","display_name":"Cross entropy","score":0.6391195058822632},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6177569627761841},{"id":"https://openalex.org/keywords/net","display_name":"Net (polyhedron)","score":0.584587812423706},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5827628374099731},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.5583881139755249},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5389173626899719},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5362986922264099},{"id":"https://openalex.org/keywords/dice","display_name":"Dice","score":0.5099679231643677},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4958103597164154},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4690544903278351},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.45742782950401306},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32693275809288025},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.10057798027992249},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10036429762840271}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8263691663742065},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.739124059677124},{"id":"https://openalex.org/C167981619","wikidata":"https://www.wikidata.org/wiki/Q1685498","display_name":"Cross entropy","level":3,"score":0.6391195058822632},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6177569627761841},{"id":"https://openalex.org/C14166107","wikidata":"https://www.wikidata.org/wiki/Q253829","display_name":"Net (polyhedron)","level":2,"score":0.584587812423706},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5827628374099731},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.5583881139755249},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5389173626899719},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5362986922264099},{"id":"https://openalex.org/C22029948","wikidata":"https://www.wikidata.org/wiki/Q45089","display_name":"Dice","level":2,"score":0.5099679231643677},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4958103597164154},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4690544903278351},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.45742782950401306},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32693275809288025},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.10057798027992249},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10036429762840271},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3446618","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3446618","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.47999998927116394}],"awards":[{"id":"https://openalex.org/G1573172955","display_name":null,"funder_award_id":"BK20200037","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G3912307594","display_name":null,"funder_award_id":"61501251, 11671004, 6193000388 and 61872424","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5083598616","display_name":null,"funder_award_id":"2018M632326","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1969013163","https://openalex.org/W1998865404","https://openalex.org/W2112796928","https://openalex.org/W2293078015","https://openalex.org/W2412782625","https://openalex.org/W2517954747","https://openalex.org/W2532206188","https://openalex.org/W2620296437","https://openalex.org/W2794825826","https://openalex.org/W2884436604","https://openalex.org/W2888538030","https://openalex.org/W2895292895","https://openalex.org/W2919115771","https://openalex.org/W2949088180","https://openalex.org/W2962914239","https://openalex.org/W2963446712","https://openalex.org/W2963881378","https://openalex.org/W2963946669","https://openalex.org/W2983050716","https://openalex.org/W3005360455","https://openalex.org/W3005538018","https://openalex.org/W3008970820","https://openalex.org/W3014304846","https://openalex.org/W3102785203","https://openalex.org/W4242177601","https://openalex.org/W4300424419"],"related_works":["https://openalex.org/W3104750253","https://openalex.org/W3021239166","https://openalex.org/W2586273397","https://openalex.org/W2390936256","https://openalex.org/W2483429559","https://openalex.org/W2016385589","https://openalex.org/W2009559548","https://openalex.org/W4200334192","https://openalex.org/W3082625452","https://openalex.org/W2377040216"],"abstract_inverted_index":{"The":[0,80,172],"U-Net":[1,33,63,74,161,166,190],"has":[2,180],"become":[3],"the":[4,31,41,48,62,90,108,118,121,125,134,142,151,159,164,177,185,188],"most":[5],"popular":[6],"structure":[7],"in":[8,12,55,77,115],"medical":[9,19],"image":[10,20],"segmentation":[11,21,44],"recent":[13],"years.":[14],"Although":[15],"its":[16],"performance":[17],"for":[18,133],"is":[22,137],"outstanding,":[23],"a":[24,68,85,96,129],"large":[25],"number":[26],"of":[27,43,58,103,110,117,120],"experiments":[28],"demonstrate":[29],"that":[30,176],"classical":[32],"network":[34,64,76,83,136,154,179],"architecture":[35,70],"seems":[36],"to":[37,88,106,139],"be":[38],"insufficient":[39],"when":[40],"size":[42],"targets":[45],"changes":[46],"and":[47,53,94,124,146,155,163,187],"imbalance":[49,143],"happens":[50],"between":[51,144],"target":[52,145],"background":[54],"different":[56,104,170],"forms":[57],"segmentation.":[59],"To":[60],"improve":[61,89],"architecture,":[65],"we":[66,149],"develop":[67],"new":[69,130],"named":[71],"densely":[72],"connected":[73],"(DenseUNet)":[75],"this":[78],"article.":[79],"proposed":[81,138,152],"DenseUNet":[82,135,153,178],"adopts":[84],"dense":[86],"block":[87,99],"feature":[91,101,111],"extraction":[92],"capability":[93],"employs":[95],"multi-feature":[97],"fuse":[98],"fusing":[100],"maps":[102],"levels":[105],"increase":[107],"accuracy":[109],"extraction.":[112],"In":[113],"addition,":[114],"view":[116],"advantages":[119],"cross":[122],"entropy":[123],"dice":[126],"loss":[127,131],"functions,":[128],"function":[132],"deal":[140],"with":[141,158,184],"background.":[147],"Finally,":[148],"test":[150],"compared":[156,183],"it":[157],"multi-resolutional":[160],"(MultiResUNet)":[162],"classic":[165,189],"networks":[167],"on":[168],"three":[169],"datasets.":[171],"experimental":[173],"results":[174],"show":[175],"significantly":[181],"performances":[182],"MultiResUNet":[186],"networks.":[191]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
