{"id":"https://openalex.org/W4313291109","doi":"https://doi.org/10.1109/access.2022.3233078","title":"Segmentation of White Blood Cells Based on CBAM-DC-UNet","display_name":"Segmentation of White Blood Cells Based on CBAM-DC-UNet","publication_year":2022,"publication_date":"2022-12-29","ids":{"openalex":"https://openalex.org/W4313291109","doi":"https://doi.org/10.1109/access.2022.3233078"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3233078","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3233078","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10003138.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10003138.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100759529","display_name":"Dongming Li","orcid":"https://orcid.org/0000-0002-5531-0618"},"institutions":[{"id":"https://openalex.org/I4210152006","display_name":"Jilin Agricultural University","ror":"https://ror.org/05dmhhd41","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152006"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dongming Li","raw_affiliation_strings":["School of Information Technology, Jilin Agricultural University, Changchun, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technology, Jilin Agricultural University, Changchun, China","institution_ids":["https://openalex.org/I4210152006"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031572653","display_name":"Shiyu Yin","orcid":"https://orcid.org/0000-0002-4401-5971"},"institutions":[{"id":"https://openalex.org/I4210152006","display_name":"Jilin Agricultural University","ror":"https://ror.org/05dmhhd41","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152006"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiyu Yin","raw_affiliation_strings":["School of Information Technology, Jilin Agricultural University, Changchun, China"],"raw_orcid":"https://orcid.org/0000-0002-4401-5971","affiliations":[{"raw_affiliation_string":"School of Information Technology, Jilin Agricultural University, Changchun, China","institution_ids":["https://openalex.org/I4210152006"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100736935","display_name":"Lei Yu","orcid":"https://orcid.org/0000-0002-7329-4631"},"institutions":[{"id":"https://openalex.org/I4210152006","display_name":"Jilin Agricultural University","ror":"https://ror.org/05dmhhd41","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152006"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Lei","raw_affiliation_strings":["School of Information Technology, Jilin Agricultural University, Changchun, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technology, Jilin Agricultural University, Changchun, China","institution_ids":["https://openalex.org/I4210152006"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088613033","display_name":"Jingning Qian","orcid":null},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"The University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jingning Qian","raw_affiliation_strings":["Faculty of Engineering and Information Technology (FEIT), The University of Melbourne, Carlton, VIC, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering and Information Technology (FEIT), The University of Melbourne, Carlton, VIC, Australia","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080791136","display_name":"Chunxi Zhao","orcid":"https://orcid.org/0009-0008-8324-003X"},"institutions":[{"id":"https://openalex.org/I4210152006","display_name":"Jilin Agricultural University","ror":"https://ror.org/05dmhhd41","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152006"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunxi Zhao","raw_affiliation_strings":["Information Center, Jilin Agricultural University, Changchun, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Center, Jilin Agricultural University, Changchun, China","institution_ids":["https://openalex.org/I4210152006"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101683953","display_name":"Lijuan Zhang","orcid":"https://orcid.org/0000-0001-7364-6070"},"institutions":[{"id":"https://openalex.org/I4385474403","display_name":"Changchun University of Technology","ror":"https://ror.org/052pakb34","country_code":null,"type":"education","lineage":["https://openalex.org/I4385474403"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lijuan Zhang","raw_affiliation_strings":["College of Computer Science and Engineering, Changchun University of Technology, Changchun, China"],"raw_orcid":"https://orcid.org/0000-0001-7364-6070","affiliations":[{"raw_affiliation_string":"College of Computer Science and Engineering, Changchun University of Technology, Changchun, China","institution_ids":["https://openalex.org/I4385474403"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100759529"],"corresponding_institution_ids":["https://openalex.org/I4210152006"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.7274,"has_fulltext":true,"cited_by_count":17,"citation_normalized_percentile":{"value":0.86024958,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"11","issue":null,"first_page":"1074","last_page":"1082"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9998000264167786,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9998000264167786,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9961000084877014,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9645000100135803,"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/segmentation","display_name":"Segmentation","score":0.6821243166923523},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6783689856529236},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6726219654083252},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5909454226493835},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5857057571411133},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5212993621826172},{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.4472542405128479},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43137598037719727},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.13553133606910706}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6821243166923523},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6783689856529236},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6726219654083252},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5909454226493835},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5857057571411133},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5212993621826172},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.4472542405128479},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43137598037719727},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.13553133606910706},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3233078","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3233078","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10003138.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:00d346d37330453aaadd429351b77494","is_oa":true,"landing_page_url":"https://doaj.org/article/00d346d37330453aaadd429351b77494","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":"IEEE Access, Vol 11, Pp 1074-1082 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3233078","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3233078","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10003138.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4000000059604645,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[{"id":"https://openalex.org/G4020718088","display_name":null,"funder_award_id":"61801439","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8232301930","display_name":null,"funder_award_id":"202107","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":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4313291109.pdf","grobid_xml":"https://content.openalex.org/works/W4313291109.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2194775991","https://openalex.org/W2412782625","https://openalex.org/W2518303809","https://openalex.org/W2523246573","https://openalex.org/W2560023338","https://openalex.org/W2563705555","https://openalex.org/W2618530766","https://openalex.org/W2630837129","https://openalex.org/W2782475589","https://openalex.org/W2787091153","https://openalex.org/W2806530968","https://openalex.org/W2884436604","https://openalex.org/W2963163009","https://openalex.org/W2963840672","https://openalex.org/W2963881378","https://openalex.org/W2968917279","https://openalex.org/W2980579679","https://openalex.org/W2989874578","https://openalex.org/W3007268491","https://openalex.org/W3088648894","https://openalex.org/W3111521801","https://openalex.org/W4206070934","https://openalex.org/W4283364477","https://openalex.org/W4285212232","https://openalex.org/W4285275205","https://openalex.org/W4289752563","https://openalex.org/W4290653854","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6727249380","https://openalex.org/W6739696289","https://openalex.org/W6767164110","https://openalex.org/W6795140394"],"related_works":["https://openalex.org/W2062399876","https://openalex.org/W2607795551","https://openalex.org/W3155117723","https://openalex.org/W1991429770","https://openalex.org/W1983892167","https://openalex.org/W2281134365","https://openalex.org/W4310746709","https://openalex.org/W4386075645","https://openalex.org/W4385574037","https://openalex.org/W2890372105"],"abstract_inverted_index":{"Monitoring":[0],"the":[1,15,59,82,91,102,107,111,114,121,124,129,133,150,154,157,161,173,177,217],"morphology":[2],"of":[3,17,51,110,123,132,180,212,219],"blood":[4,33,181,202],"leukocytes,":[5,182,203],"plays":[6],"an":[7,52,94],"important":[8],"role":[9],"in":[10,14,62,67,90,216],"medical":[11],"research,":[12],"especially":[13],"treatment":[16],"diseases":[18],"such":[19],"as":[20],"immunodeficiency.":[21],"Traditional":[22],"manual":[23],"detection":[24,215],"methods":[25],"are":[26,35,78],"susceptible":[27],"to":[28,100,119],"numerous":[29],"interference":[30],"factors.":[31],"Therefore,":[32],"cells":[34],"often":[36],"segmented":[37,201],"using":[38],"deep-learning":[39],"algorithms.":[40],"This":[41],"study":[42],"proposes":[43],"a":[44,49,63,68,146,209],"U-Net":[45,175],"model":[46],"based":[47],"on":[48,149],"combination":[50],"attention":[53,95],"mechanism":[54,96],"and":[55,75,105,153,188,195,221],"dilated":[56,73],"convolutions.":[57],"First,":[58],"traditional":[60],"convolution":[61,88],"double":[64],"convolutional":[65],"module":[66,97],"network":[69],"is":[70,98],"replaced":[71],"by":[72,80,192],"convolution,":[74],"multi-scale":[76],"features":[77,104],"obtained":[79],"expanding":[81],"receptive":[83],"field.":[84],"Second,":[85],"after":[86],"each":[87],"layer":[89],"upsampling":[92],"layer,":[93],"combined":[99],"refine":[101],"adaptive":[103],"improve":[106],"segmentation":[108,151,178],"performance":[109],"model.":[112],"Finally,":[113],"RAdam":[115],"optimizer":[116],"was":[117,138,156],"used":[118,207],"enhance":[120],"robustness":[122],"learning":[125],"rate":[126],"variations.":[127],"Through":[128],"ablation":[130],"experiment":[131],"three":[134,142,162],"improvement":[135,143,155],"directions,":[136],"it":[137],"concluded":[139],"that":[140,170],"all":[141],"directions":[144],"had":[145],"positive":[147],"effect":[148],"result,":[152],"most":[158],"effective":[159],"when":[160],"improvements":[163],"were":[164,190],"combined.":[165],"The":[166],"experimental":[167],"results":[168],"show":[169],"compared":[171],"with":[172],"original":[174],"model,":[176],"indicators":[179],"intersection":[183],"over":[184],"union":[185],"(IOU),":[186],"recall":[187],"accuracy":[189],"increased":[191],"5.1%,":[193],"5.7%":[194],"1.2%,":[196],"respectively,":[197],"which":[198,204],"more":[199],"accurately":[200],"may":[205],"be":[206],"for":[208],"greater":[210],"degree":[211],"auxiliary":[213],"leukocyte":[214],"application":[218],"immunodeficiency":[220],"other":[222],"diseases.":[223]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}