{"id":"https://openalex.org/W4200621093","doi":"https://doi.org/10.1109/wcsp52459.2021.9613613","title":"A medical image segmentation method based on multi-scale feature extraction","display_name":"A medical image segmentation method based on multi-scale feature extraction","publication_year":2021,"publication_date":"2021-10-20","ids":{"openalex":"https://openalex.org/W4200621093","doi":"https://doi.org/10.1109/wcsp52459.2021.9613613"},"language":"en","primary_location":{"id":"doi:10.1109/wcsp52459.2021.9613613","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcsp52459.2021.9613613","pdf_url":null,"source":{"id":"https://openalex.org/S4363607893","display_name":"2021 13th International Conference on Wireless Communications and Signal Processing (WCSP)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 13th International Conference on Wireless Communications and Signal Processing (WCSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100675943","display_name":"Rong Zhao","orcid":"https://orcid.org/0000-0002-2320-0326"},"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":"Rong Zhao","raw_affiliation_strings":["School of Communication and Information Engineering Nanjing University of Posts and Telecommunications, Nanjing, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering Nanjing University of Posts and Telecommunications, Nanjing, P. R. China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064993870","display_name":"Weidan Yan","orcid":"https://orcid.org/0000-0002-0089-5882"},"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":"Weidan Yan","raw_affiliation_strings":["School of Internet of Things Nanjing University of Posts and Telecommunications, Nanjing, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Internet of Things Nanjing University of Posts and Telecommunications, Nanjing, P. R. China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027195747","display_name":"Chao Zhou","orcid":"https://orcid.org/0000-0001-6528-3257"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Chao Zhou","raw_affiliation_strings":["National University of Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076984228","display_name":"Dengyin Zhang","orcid":"https://orcid.org/0000-0001-6080-6151"},"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":"Dengyin Zhang","raw_affiliation_strings":["School of Communication and Information Engineering Nanjing University of Posts and Telecommunications, Nanjing, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering Nanjing University of Posts and Telecommunications, Nanjing, P. R. China","institution_ids":["https://openalex.org/I41198531"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"17","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","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/T11438","display_name":"Retinal Imaging and Analysis","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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9994999766349792,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9977999925613403,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8153312802314758},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6611582040786743},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6446826457977295},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6409876942634583},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.6137523651123047},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5824379324913025},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5481727719306946},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5468324422836304},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5113046169281006},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4914654493331909},{"id":"https://openalex.org/keywords/net","display_name":"Net (polyhedron)","score":0.48094505071640015},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.403373122215271},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3344041109085083},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.14089426398277283},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10077762603759766}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8153312802314758},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6611582040786743},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6446826457977295},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6409876942634583},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.6137523651123047},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5824379324913025},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5481727719306946},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5468324422836304},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5113046169281006},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4914654493331909},{"id":"https://openalex.org/C14166107","wikidata":"https://www.wikidata.org/wiki/Q253829","display_name":"Net (polyhedron)","level":2,"score":0.48094505071640015},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.403373122215271},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3344041109085083},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.14089426398277283},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10077762603759766},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/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/wcsp52459.2021.9613613","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcsp52459.2021.9613613","pdf_url":null,"source":{"id":"https://openalex.org/S4363607893","display_name":"2021 13th International Conference on Wireless Communications and Signal Processing (WCSP)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 13th International Conference on Wireless Communications and Signal Processing (WCSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.5199999809265137}],"awards":[{"id":"https://openalex.org/G4439784669","display_name":"\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u5927\u6c14\u6563\u5c04\u65b0\u6a21\u578b\u4e0e\u56fe\u50cf\u53bb\u96fe\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61872423","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2119496927","https://openalex.org/W2327084999","https://openalex.org/W2607394097","https://openalex.org/W2630837129","https://openalex.org/W2791680898","https://openalex.org/W2794990008","https://openalex.org/W2948537313","https://openalex.org/W2963239200","https://openalex.org/W3025800305","https://openalex.org/W3091595271","https://openalex.org/W6639824700","https://openalex.org/W6701629809","https://openalex.org/W6741332042"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W2900413183","https://openalex.org/W4390975304","https://openalex.org/W147410782","https://openalex.org/W3022252430","https://openalex.org/W4287804464","https://openalex.org/W3103989898","https://openalex.org/W3211292372","https://openalex.org/W803346624"],"abstract_inverted_index":{"Medical":[0],"image":[1],"segment":[2,13,48,71,81],"is":[3,14,19],"considered":[4],"as":[5],"an":[6,15],"important":[7],"technology":[8],"in":[9,41,60,105,114],"clinical":[10],"diagnosis.":[11],"Manual":[12],"accurate":[16,30],"method":[17],"but":[18],"too":[20],"time-consuming":[21],"and":[22,29,57,137],"laborious.":[23],"Hence":[24],"how":[25],"to":[26,54,68,100],"realize":[27],"fast":[28],"automatic":[31],"segmentation":[32,147],"with":[33,92],"deep":[34],"learning":[35],"has":[36],"been":[37],"attached":[38],"more":[39],"importance":[40],"recent":[42],"years.":[43],"In":[44],"view":[45],"of":[46,117],"most":[47],"model":[49,67],"loses":[50],"detailed":[51],"information":[52,112],"due":[53],"the":[55,70,101,108,115],"convolution":[56,89],"pooling":[58],"operations,":[59],"this":[61],"paper,":[62],"we":[63],"propose":[64],"a":[65],"new":[66],"improve":[69],"result":[72],"by":[73,94],"extracting":[74],"multi-scale":[75,87],"feature":[76,103],"at":[77],"each":[78],"stage.":[79,98],"Our":[80],"model,":[82],"called":[83],"mixed-net,":[84],"combines":[85],"our":[86,150],"dilated":[88],"module":[90],"(MDCM)":[91],"u-net":[93,155],"skip":[95,128],"connections":[96],"across":[97],"Due":[99],"sufficient":[102],"extraction":[104],"shallow":[106,136],"layers,":[107],"mixed-net":[109,151],"can":[110,131],"reduce":[111],"loss":[113],"processing":[116],"training":[118,157],"data":[119,160],"without":[120],"increasing":[121],"network":[122],"size":[123],"greatly.":[124],"Using":[125],"MDCM":[126],"before":[127],"connection":[129],"also":[130],"bridge":[132],"semantic":[133],"gap":[134],"between":[135],"deeper":[138],"layers.":[139],"The":[140],"experiments":[141],"on":[142,158],"retinal":[143],"blood":[144],"vessels":[145],"images":[146],"shows":[148],"that":[149],"performs":[152],"better":[153],"than":[154],"after":[156],"DRIVE":[159],"sets.":[161]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}