{"id":"https://openalex.org/W4389780785","doi":"https://doi.org/10.1145/3627341.3627343","title":"DA-UNet: Deformable Attention U-Net for Nucleus Segmentation","display_name":"DA-UNet: Deformable Attention U-Net for Nucleus Segmentation","publication_year":2023,"publication_date":"2023-08-25","ids":{"openalex":"https://openalex.org/W4389780785","doi":"https://doi.org/10.1145/3627341.3627343"},"language":"en","primary_location":{"id":"doi:10.1145/3627341.3627343","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3627341.3627343","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 International Conference on Computer, Vision and Intelligent Technology","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/A5076766949","display_name":"Bin Xiao","orcid":"https://orcid.org/0009-0006-6342-9244"},"institutions":[{"id":"https://openalex.org/I165745306","display_name":"Southwest Petroleum University","ror":"https://ror.org/03h17x602","country_code":"CN","type":"education","lineage":["https://openalex.org/I165745306"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bin Xiao","raw_affiliation_strings":["Southwest Petroleum University, China"],"raw_orcid":"https://orcid.org/0009-0006-6342-9244","affiliations":[{"raw_affiliation_string":"Southwest Petroleum University, China","institution_ids":["https://openalex.org/I165745306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101480470","display_name":"Yunfeng Pan","orcid":"https://orcid.org/0009-0008-2844-2229"},"institutions":[{"id":"https://openalex.org/I165745306","display_name":"Southwest Petroleum University","ror":"https://ror.org/03h17x602","country_code":"CN","type":"education","lineage":["https://openalex.org/I165745306"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunfeng Pan","raw_affiliation_strings":["Southwest Petroleum University, China"],"raw_orcid":"https://orcid.org/0009-0008-2844-2229","affiliations":[{"raw_affiliation_string":"Southwest Petroleum University, China","institution_ids":["https://openalex.org/I165745306"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067983994","display_name":"Xingpeng Zhang","orcid":"https://orcid.org/0000-0001-6547-6374"},"institutions":[{"id":"https://openalex.org/I165745306","display_name":"Southwest Petroleum University","ror":"https://ror.org/03h17x602","country_code":"CN","type":"education","lineage":["https://openalex.org/I165745306"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingpeng Zhang","raw_affiliation_strings":["Southwest Petroleum University, China"],"raw_orcid":"https://orcid.org/0000-0001-6547-6374","affiliations":[{"raw_affiliation_string":"Southwest Petroleum University, China","institution_ids":["https://openalex.org/I165745306"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5076766949"],"corresponding_institution_ids":["https://openalex.org/I165745306"],"apc_list":null,"apc_paid":null,"fwci":0.3532,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.61178252,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9997000098228455,"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":0.9997000098228455,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T12874","display_name":"Digital Imaging for Blood Diseases","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"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.8072757124900818},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.730983555316925},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7143905162811279},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6403835415840149},{"id":"https://openalex.org/keywords/nucleus","display_name":"Nucleus","score":0.6371785402297974},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5168857574462891},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4919604957103729},{"id":"https://openalex.org/keywords/net","display_name":"Net (polyhedron)","score":0.46119120717048645},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33646753430366516},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1874276101589203},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13584944605827332},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.08436059951782227},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.06765633821487427},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.05488583445549011}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8072757124900818},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.730983555316925},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7143905162811279},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6403835415840149},{"id":"https://openalex.org/C2780723820","wikidata":"https://www.wikidata.org/wiki/Q1934178","display_name":"Nucleus","level":2,"score":0.6371785402297974},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5168857574462891},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4919604957103729},{"id":"https://openalex.org/C14166107","wikidata":"https://www.wikidata.org/wiki/Q253829","display_name":"Net (polyhedron)","level":2,"score":0.46119120717048645},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33646753430366516},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1874276101589203},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13584944605827332},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.08436059951782227},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.06765633821487427},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.05488583445549011}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3627341.3627343","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3627341.3627343","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 International Conference on Computer, Vision and Intelligent Technology","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2432481613","https://openalex.org/W2601564443","https://openalex.org/W2798122215","https://openalex.org/W3111124458","https://openalex.org/W3138516171","https://openalex.org/W3172876541","https://openalex.org/W4221145209","https://openalex.org/W4283755958","https://openalex.org/W4319216049","https://openalex.org/W4382998948","https://openalex.org/W6750469568"],"related_works":["https://openalex.org/W2912321008","https://openalex.org/W2324368075","https://openalex.org/W1998607122","https://openalex.org/W2972032537","https://openalex.org/W338149487","https://openalex.org/W2112693048","https://openalex.org/W3154107650","https://openalex.org/W2613671004","https://openalex.org/W2890372105","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Abstract:":[0],"Cell":[1],"nucleus":[2,42],"segmentation":[3],"plays":[4],"a":[5,32,53],"significant":[6],"role":[7],"in":[8],"Computer-Aided":[9],"systems":[10],"for":[11],"cancer":[12],"diagnosis.":[13],"However,":[14],"complex":[15,43],"visual":[16,44],"features,":[17],"such":[18],"as":[19],"blurring":[20],"and":[21,71,81],"irregular":[22],"shapes,":[23],"increase":[24],"the":[25,39,48,62,68,76,86],"difficulty":[26],"of":[27,41],"segmentation.":[28],"This":[29],"paper":[30],"proposes":[31],"deformable":[33,54,72],"attention":[34,55,69],"U-Net":[35],"(DA-UNet)":[36],"to":[37,60],"enhance":[38],"learning":[40],"features.":[45],"Based":[46],"on":[47,75],"traditional":[49],"U-Net,":[50],"we":[51],"introduce":[52],"(DA)":[56],"module,":[57],"which":[58],"aims":[59],"learn":[61],"more":[63],"suitable":[64],"shape":[65],"features":[66],"by":[67],"mechanism":[70],"convolution.":[73],"Experiments":[74],"2018":[77],"Data":[78],"Science":[79],"Bowl":[80],"MoNuSeg":[82],"datasets":[83],"show":[84],"that":[85],"proposed":[87],"DA-UNet":[88],"can":[89],"achieve":[90],"good":[91],"results.":[92]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}