{"id":"https://openalex.org/W4406260332","doi":"https://doi.org/10.1109/bibm62325.2024.10822438","title":"Multi-Scale Co-Attention Reinforced U-Net for Medical Image Segmentation","display_name":"Multi-Scale Co-Attention Reinforced U-Net for Medical Image Segmentation","publication_year":2024,"publication_date":"2024-12-03","ids":{"openalex":"https://openalex.org/W4406260332","doi":"https://doi.org/10.1109/bibm62325.2024.10822438"},"language":"en","primary_location":{"id":"doi:10.1109/bibm62325.2024.10822438","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822438","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-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/A5103269662","display_name":"Yantao Song","orcid":"https://orcid.org/0000-0001-9017-9603"},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yantao Song","raw_affiliation_strings":["Shanxi University,Institute of Big Data Science and Industry,Taiyuan,China"],"affiliations":[{"raw_affiliation_string":"Shanxi University,Institute of Big Data Science and Industry,Taiyuan,China","institution_ids":["https://openalex.org/I181877577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100376495","display_name":"Miao Zhang","orcid":"https://orcid.org/0000-0003-3582-6075"},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Miao Zhang","raw_affiliation_strings":["Shanxi University,Institute of Big Data Science and Industry,Taiyuan,China"],"affiliations":[{"raw_affiliation_string":"Shanxi University,Institute of Big Data Science and Industry,Taiyuan,China","institution_ids":["https://openalex.org/I181877577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111162470","display_name":"Yunli Lu","orcid":"https://orcid.org/0009-0000-2460-7526"},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunli Lu","raw_affiliation_strings":["Shanxi University,Institute of Big Data Science and Industry,Taiyuan,China"],"affiliations":[{"raw_affiliation_string":"Shanxi University,Institute of Big Data Science and Industry,Taiyuan,China","institution_ids":["https://openalex.org/I181877577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062987221","display_name":"Jiang Chang","orcid":"https://orcid.org/0000-0003-1462-6541"},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiang Chang","raw_affiliation_strings":["Shanxi University,Institute of Big Data Science and Industry,Taiyuan,China"],"affiliations":[{"raw_affiliation_string":"Shanxi University,Institute of Big Data Science and Industry,Taiyuan,China","institution_ids":["https://openalex.org/I181877577"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100432078","display_name":"Lu Chen","orcid":"https://orcid.org/0000-0002-2184-8268"},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lu Chen","raw_affiliation_strings":["Shanxi University,Institute of Big Data Science and Industry,Taiyuan,China"],"affiliations":[{"raw_affiliation_string":"Shanxi University,Institute of Big Data Science and Industry,Taiyuan,China","institution_ids":["https://openalex.org/I181877577"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5103269662"],"corresponding_institution_ids":["https://openalex.org/I181877577"],"apc_list":null,"apc_paid":null,"fwci":0.5263,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.68809945,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2422","last_page":"2429"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.970300018787384,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.970300018787384,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.968999981880188,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.949999988079071,"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/scale","display_name":"Scale (ratio)","score":0.6006582975387573},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5881295204162598},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5728205442428589},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4788234531879425},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.43895265460014343},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.43344181776046753},{"id":"https://openalex.org/keywords/net","display_name":"Net (polyhedron)","score":0.4272499084472656},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3873363435268402},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11718636751174927},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.10027644038200378},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08400323987007141}],"concepts":[{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.6006582975387573},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5881295204162598},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5728205442428589},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4788234531879425},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.43895265460014343},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.43344181776046753},{"id":"https://openalex.org/C14166107","wikidata":"https://www.wikidata.org/wiki/Q253829","display_name":"Net (polyhedron)","level":2,"score":0.4272499084472656},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3873363435268402},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11718636751174927},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.10027644038200378},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08400323987007141},{"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:10.1109/bibm62325.2024.10822438","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822438","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321884","display_name":"Shanxi Scholarship Council of China","ror":"https://ror.org/04atp4p48"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2142332605","https://openalex.org/W2618530766","https://openalex.org/W2774320778","https://openalex.org/W2884436604","https://openalex.org/W2963946669","https://openalex.org/W2991372685","https://openalex.org/W2997286550","https://openalex.org/W3004868960","https://openalex.org/W3004890872","https://openalex.org/W3026743644","https://openalex.org/W3030515889","https://openalex.org/W3032638707","https://openalex.org/W3116714234","https://openalex.org/W3165252795","https://openalex.org/W3177052299","https://openalex.org/W3203480968","https://openalex.org/W3216277748","https://openalex.org/W4312443924","https://openalex.org/W4321232185","https://openalex.org/W6750469568","https://openalex.org/W6790275670","https://openalex.org/W6801589178"],"related_works":["https://openalex.org/W2912321008","https://openalex.org/W1998607122","https://openalex.org/W2324368075","https://openalex.org/W2972124131","https://openalex.org/W338149487","https://openalex.org/W4403012196","https://openalex.org/W2972032537","https://openalex.org/W150363521","https://openalex.org/W3154107650","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Medical":[0],"image":[1,119,133],"segmentation":[2,27],"plays":[3],"a":[4,64,76,93],"crucial":[5],"role":[6],"in":[7,22,37,127],"classifying":[8],"anatomical":[9],"structures":[10,24],"for":[11],"clinical":[12],"analysis":[13],"and":[14,20,56,72,82,125],"intervention.":[15],"However,":[16],"the":[17,70,129],"inherent":[18],"variability":[19],"complexity":[21],"target":[23],"make":[25],"accurate":[26],"tasks":[28],"challenging.":[29],"Traditional":[30],"convolutional":[31,47,88],"networks":[32],"(e.g.,":[33,49],"U-Net)":[34],"have":[35],"limitations":[36],"feature":[38,99],"extraction":[39],"due":[40],"to":[41],"small":[42],"receptive":[43],"fields,":[44],"while":[45],"larger":[46],"kernels":[48],"ConvNeXt)":[50],"struggle":[51],"with":[52],"local":[53,83],"context":[54],"modeling":[55],"risk":[57],"overfitting.":[58],"In":[59],"this":[60],"paper,":[61],"we":[62,91],"propose":[63],"multi-scale":[65,87],"reinforced":[66],"U-Net":[67,71],"that":[68,96],"integrates":[69],"ConvNeXt":[73],"architectures":[74],"as":[75],"dual-channel":[77],"encoder,":[78],"capturing":[79],"both":[80],"global":[81],"features":[84],"simultaneously":[85],"through":[86],"kernels.":[89],"Specifically,":[90],"designed":[92],"co-attention":[94],"module":[95],"achieves":[97],"effective":[98],"fusion":[100],"across":[101],"different":[102],"scales":[103],"by":[104],"embedding":[105],"positional":[106],"information":[107],"into":[108],"channel":[109],"attention.":[110],"Our":[111],"approach":[112],"demonstrates":[113],"state-of-the-art":[114],"performance":[115],"on":[116],"multiple":[117],"medical":[118,132],"datasets,":[120],"highlighting":[121],"its":[122],"effectiveness,":[123],"superiority,":[124],"generalizability":[126],"addressing":[128],"complexities":[130],"of":[131],"segmentation.":[134]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}