{"id":"https://openalex.org/W4406260608","doi":"https://doi.org/10.1109/bibm62325.2024.10822831","title":"CSA-UNet: An Efficient Context Separable Attention UNet for Medical Image Segmentation","display_name":"CSA-UNet: An Efficient Context Separable Attention UNet for Medical Image Segmentation","publication_year":2024,"publication_date":"2024-12-03","ids":{"openalex":"https://openalex.org/W4406260608","doi":"https://doi.org/10.1109/bibm62325.2024.10822831"},"language":"en","primary_location":{"id":"doi:10.1109/bibm62325.2024.10822831","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822831","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/A5061397277","display_name":"Xiangqiong Wu","orcid":"https://orcid.org/0000-0001-7577-0534"},"institutions":[{"id":"https://openalex.org/I916048824","display_name":"Hunan First Normal University","ror":"https://ror.org/00s9d1a36","country_code":"CN","type":"education","lineage":["https://openalex.org/I916048824"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangqiong Wu","raw_affiliation_strings":["Hunan First Normal University,School of Computer Science,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hunan First Normal University,School of Computer Science,Changsha,China","institution_ids":["https://openalex.org/I916048824"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015980953","display_name":"Nan Hu","orcid":"https://orcid.org/0000-0002-7505-5001"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nan Hu","raw_affiliation_strings":["Sun Yat-sen University,School of Computer Science and Engineering,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,School of Computer Science and Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101779357","display_name":"Peng Wang","orcid":"https://orcid.org/0000-0003-0278-7743"},"institutions":[{"id":"https://openalex.org/I916048824","display_name":"Hunan First Normal University","ror":"https://ror.org/00s9d1a36","country_code":"CN","type":"education","lineage":["https://openalex.org/I916048824"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Wang","raw_affiliation_strings":["Hunan First Normal University,School of Electronic Information,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hunan First Normal University,School of Electronic Information,Changsha,China","institution_ids":["https://openalex.org/I916048824"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4375,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.6526844,"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":"2688","last_page":"2693"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9846000075340271,"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":0.9846000075340271,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.9837999939918518,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9812999963760376,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6861240267753601},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6853967308998108},{"id":"https://openalex.org/keywords/separable-space","display_name":"Separable space","score":0.6840394139289856},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5966266393661499},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5581181645393372},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.52044278383255},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.46740275621414185},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1596147119998932}],"concepts":[{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6861240267753601},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6853967308998108},{"id":"https://openalex.org/C70710897","wikidata":"https://www.wikidata.org/wiki/Q680081","display_name":"Separable space","level":2,"score":0.6840394139289856},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5966266393661499},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5581181645393372},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.52044278383255},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.46740275621414185},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1596147119998932},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm62325.2024.10822831","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822831","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/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322843","display_name":"Natural Science Foundation of\u00a0Hunan Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2395611524","https://openalex.org/W2412782625","https://openalex.org/W2963881378","https://openalex.org/W2991372685","https://openalex.org/W2996290406","https://openalex.org/W3025407526","https://openalex.org/W3138516171","https://openalex.org/W3164174046","https://openalex.org/W3204614423","https://openalex.org/W4295934721","https://openalex.org/W4309344151","https://openalex.org/W4312847199","https://openalex.org/W4315630813","https://openalex.org/W4384159609","https://openalex.org/W4385245566","https://openalex.org/W4386350424","https://openalex.org/W4388841096","https://openalex.org/W4401749301","https://openalex.org/W6750469568","https://openalex.org/W6790275670","https://openalex.org/W6797399245","https://openalex.org/W6798837711","https://openalex.org/W6811014117"],"related_works":["https://openalex.org/W2009525028","https://openalex.org/W4321064619","https://openalex.org/W2076561698","https://openalex.org/W2053599029","https://openalex.org/W2962925412","https://openalex.org/W2023672523","https://openalex.org/W4246719751","https://openalex.org/W2483165346","https://openalex.org/W3011179836","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Accurate":[0],"segmentation":[1,29,36,75,126,147,160],"of":[2,23,119,146],"lesions":[3],"in":[4,51,76,144,158],"medical":[5,24,77],"images":[6],"is":[7],"crucial":[8],"for":[9,73],"early":[10],"diagnosis":[11],"and":[12,40,86,93,96,128,149],"treatment,":[13],"significantly":[14],"improving":[15],"patient":[16],"survival":[17],"rates.":[18],"However,":[19],"the":[20,47,52,102,111,117,137,141,163],"inherent":[21],"characteristics":[22],"imaging":[25],"render":[26],"precise":[27],"lesion":[28,74,159],"a":[30],"highly":[31],"challenging":[32],"task.":[33],"Traditional":[34],"manual":[35],"methods":[37],"are":[38],"time-consuming":[39],"heavily":[41],"dependent":[42],"on":[43],"expert":[44],"knowledge,":[45],"while":[46,115,161],"standard":[48],"convolutions":[49],"used":[50],"U-Net":[53,71,143],"model":[54,72,80,139],"fail":[55],"to":[56,91,124],"capture":[57],"sufficient":[58],"contextual":[59,98],"information.":[60],"To":[61],"address":[62],"these":[63],"challenges,":[64],"we":[65],"propose":[66],"an":[67],"enhanced":[68],"context-separable":[69],"attention":[70,122],"images.":[78],"This":[79],"introduces":[81],"Separable":[82],"Attention":[83,88],"(SA)":[84],"block":[85,90],"Context":[87],"(CA)":[89],"extract":[92],"integrate":[94],"local":[95],"global":[97],"information,":[99],"thereby":[100],"enhancing":[101],"model\u2019s":[103,112,164],"feature":[104],"extraction":[105],"capabilities.":[106],"The":[107],"proposed":[108,138],"method":[109],"increases":[110],"receptive":[113],"field":[114],"reducing":[116,162],"number":[118],"parameters,":[120],"incorporating":[121],"mechanisms":[123],"improve":[125],"accuracy":[127,148],"efficiency.":[129],"Experimental":[130],"results":[131],"across":[132],"various":[133],"datasets":[134],"demonstrate":[135],"that":[136],"outperforms":[140],"original":[142],"terms":[145],"efficiency,":[150],"achieving":[151],"higher":[152],"mean":[153],"Intersection":[154],"over":[155],"Union":[156],"values":[157],"parameters.":[165]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
