{"id":"https://openalex.org/W7116951955","doi":"https://doi.org/10.1109/access.2025.3647597","title":"MSDA-UNet: Dynamic Fusion and Attention for Enhanced UNet Abdominal Multi-Organ Segmentation on Synapse","display_name":"MSDA-UNet: Dynamic Fusion and Attention for Enhanced UNet Abdominal Multi-Organ Segmentation on Synapse","publication_year":2025,"publication_date":"2025-12-23","ids":{"openalex":"https://openalex.org/W7116951955","doi":"https://doi.org/10.1109/access.2025.3647597"},"language":null,"primary_location":{"id":"doi:10.1109/access.2025.3647597","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3647597","pdf_url":null,"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://doi.org/10.1109/access.2025.3647597","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5121079064","display_name":"Zhigao Zeng","orcid":null},"institutions":[{"id":"https://openalex.org/I49934816","display_name":"Hunan University of Technology","ror":"https://ror.org/04j3vr751","country_code":"CN","type":"education","lineage":["https://openalex.org/I49934816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhigao Zeng","raw_affiliation_strings":["College of Computer and Artificial Intelligence, Hunan University of Technology, Tianyuan, Zhuzhou, Hunan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer and Artificial Intelligence, Hunan University of Technology, Tianyuan, Zhuzhou, Hunan, China","institution_ids":["https://openalex.org/I49934816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004003845","display_name":"Yuming Du","orcid":null},"institutions":[{"id":"https://openalex.org/I49934816","display_name":"Hunan University of Technology","ror":"https://ror.org/04j3vr751","country_code":"CN","type":"education","lineage":["https://openalex.org/I49934816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuming Du","raw_affiliation_strings":["College of Computer and Artificial Intelligence, Hunan University of Technology, Tianyuan, Zhuzhou, Hunan, China"],"raw_orcid":"https://orcid.org/0009-0002-3618-8378","affiliations":[{"raw_affiliation_string":"College of Computer and Artificial Intelligence, Hunan University of Technology, Tianyuan, Zhuzhou, Hunan, China","institution_ids":["https://openalex.org/I49934816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004706129","display_name":"Shengqiu Yi","orcid":null},"institutions":[{"id":"https://openalex.org/I49934816","display_name":"Hunan University of Technology","ror":"https://ror.org/04j3vr751","country_code":"CN","type":"education","lineage":["https://openalex.org/I49934816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengqiu Yi","raw_affiliation_strings":["College of Computer and Artificial Intelligence, Hunan University of Technology, Tianyuan, Zhuzhou, Hunan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer and Artificial Intelligence, Hunan University of Technology, Tianyuan, Zhuzhou, Hunan, China","institution_ids":["https://openalex.org/I49934816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089592676","display_name":"Xinpan Yuan","orcid":"https://orcid.org/0000-0001-9509-0755"},"institutions":[{"id":"https://openalex.org/I49934816","display_name":"Hunan University of Technology","ror":"https://ror.org/04j3vr751","country_code":"CN","type":"education","lineage":["https://openalex.org/I49934816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinpan Yuan","raw_affiliation_strings":["College of Computer and Artificial Intelligence, Hunan University of Technology, Tianyuan, Zhuzhou, Hunan, China"],"raw_orcid":"https://orcid.org/0000-0002-1672-683X","affiliations":[{"raw_affiliation_string":"College of Computer and Artificial Intelligence, Hunan University of Technology, Tianyuan, Zhuzhou, Hunan, China","institution_ids":["https://openalex.org/I49934816"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121081812","display_name":"Qiang Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I49934816","display_name":"Hunan University of Technology","ror":"https://ror.org/04j3vr751","country_code":"CN","type":"education","lineage":["https://openalex.org/I49934816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Liu","raw_affiliation_strings":["College of Computer and Artificial Intelligence, Hunan University of Technology, Tianyuan, Zhuzhou, Hunan, China"],"raw_orcid":"https://orcid.org/0000-0001-8701-8737","affiliations":[{"raw_affiliation_string":"College of Computer and Artificial Intelligence, Hunan University of Technology, Tianyuan, Zhuzhou, Hunan, China","institution_ids":["https://openalex.org/I49934816"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I49934816"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.52019386,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"1027","last_page":"1040"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.800000011920929,"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":0.800000011920929,"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":0.054099999368190765,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.03240000084042549,"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/convolution","display_name":"Convolution (computer science)","score":0.6473000049591064},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6403999924659729},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6154000163078308},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5796999931335449},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5586000084877014},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4408000111579895},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42719998955726624},{"id":"https://openalex.org/keywords/hausdorff-distance","display_name":"Hausdorff distance","score":0.40299999713897705},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.39419999718666077}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8185999989509583},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.680899977684021},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6473000049591064},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6403999924659729},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6154000163078308},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5796999931335449},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5586000084877014},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4408000111579895},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42719998955726624},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4074000120162964},{"id":"https://openalex.org/C141898687","wikidata":"https://www.wikidata.org/wiki/Q1501997","display_name":"Hausdorff distance","level":2,"score":0.40299999713897705},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.39419999718666077},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.38440001010894775},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.3765000104904175},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.34950000047683716},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.3287999927997589},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3127000033855438},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.3000999987125397},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.2944999933242798},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.2849999964237213},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.28189998865127563},{"id":"https://openalex.org/C194980680","wikidata":"https://www.wikidata.org/wiki/Q245450","display_name":"Circular convolution","level":5,"score":0.27379998564720154},{"id":"https://openalex.org/C13540734","wikidata":"https://www.wikidata.org/wiki/Q5318996","display_name":"Dynamic network analysis","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.257099986076355}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/access.2025.3647597","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3647597","pdf_url":null,"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"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3647597","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3647597","pdf_url":null,"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":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7556822896003723}],"awards":[{"id":"https://openalex.org/G174463083","display_name":null,"funder_award_id":"2024JJ9550","funder_id":"https://openalex.org/F4320322843","funder_display_name":"Natural Science Foundation of\u00a0Hunan Province"},{"id":"https://openalex.org/G2214395651","display_name":"\u5de5\u4e1a\u667a\u80fd\u70e7\u7ed3\u7089\u4e91\u5e73\u53f0\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"2025JJ70028","funder_id":"https://openalex.org/F4320322843","funder_display_name":"Natural Science Foundation of\u00a0Hunan Province"},{"id":"https://openalex.org/G8297447497","display_name":"\u89c6\u89c9\u5173\u7cfb\u68c0\u6d4b\u9a71\u52a8\u7684\u5185\u7aa5\u955c\u4e0b\u817a\u6837\u4f53\u5206\u5272\u5206\u7ea7\u7814\u7a76","funder_award_id":"2025JJ81178","funder_id":"https://openalex.org/F4320322843","funder_display_name":"Natural Science Foundation of\u00a0Hunan Province"},{"id":"https://openalex.org/G8685637886","display_name":"\u57fa\u4e8e\u591a\u6a21\u6001\u77e5\u8bc6\u56fe\u8c31\u7684\u5728\u7ebf\u8d44\u6e90\u667a\u80fd\u63a8\u8350\u6280\u672f\u7814\u7a76","funder_award_id":"2025JJ70071","funder_id":"https://openalex.org/F4320322843","funder_display_name":"Natural Science Foundation of\u00a0Hunan Province"},{"id":"https://openalex.org/G917387035","display_name":null,"funder_award_id":"24A0401","funder_id":"https://openalex.org/F4320311213","funder_display_name":"Education Department of Hunan Province"}],"funders":[{"id":"https://openalex.org/F4320311213","display_name":"Education Department of Hunan Province","ror":"https://ror.org/05ckg3w11"},{"id":"https://openalex.org/F4320322843","display_name":"Natural Science Foundation of\u00a0Hunan Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1836465849","https://openalex.org/W1901129140","https://openalex.org/W1909740415","https://openalex.org/W2008359794","https://openalex.org/W2156163116","https://openalex.org/W2160754664","https://openalex.org/W2560328367","https://openalex.org/W2752782242","https://openalex.org/W2884436604","https://openalex.org/W2889985731","https://openalex.org/W2923997689","https://openalex.org/W2932083555","https://openalex.org/W2963351448","https://openalex.org/W3034421924","https://openalex.org/W3035367255","https://openalex.org/W3035678286","https://openalex.org/W3112256294","https://openalex.org/W3127751679","https://openalex.org/W3197957534","https://openalex.org/W3212933375","https://openalex.org/W4254751698","https://openalex.org/W4289752563","https://openalex.org/W4312428231","https://openalex.org/W4312794844","https://openalex.org/W4312812783","https://openalex.org/W4312881242","https://openalex.org/W4320728002","https://openalex.org/W4396544473","https://openalex.org/W4402855435"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"segmentation":[1],"of":[2,81,111,177],"medical":[3],"images":[4],"is":[5],"crucial":[6],"for":[7],"quantitative":[8],"analysis":[9],"and":[10,15,32,44,83,92,121,131,140,156,174],"treatment":[11],"planning.":[12],"Although":[13],"U-Net":[14,57,166],"its":[16],"attention-enhanced":[17],"variants":[18],"have":[19],"achieved":[20],"strong":[21],"results,":[22],"they":[23],"often":[24],"do":[25],"not":[26],"fully":[27],"exploit":[28],"multi-scale":[29],"contextual":[30],"information":[31],"still":[33],"rely":[34],"on":[35,88],"static":[36],"convolutional":[37],"kernels,":[38],"which":[39],"limits":[40],"adaptability":[41],"to":[42,127],"complex":[43],"deformable":[45],"anatomy.":[46],"To":[47],"address":[48],"these":[49],"limitations,":[50],"we":[51,63],"propose":[52],"a":[53,73,94,101],"Multi-Scale":[54,65],"Dynamic":[55,66],"Attention":[56,67],"(MSDA-UNet).":[58],"At":[59],"critical":[60],"skip":[61],"connections,":[62],"insert":[64],"(MSDA)":[68],"modules,":[69],"each":[70],"comprising:":[71],"(i)":[72],"dynamic":[74,104],"convolution":[75,105],"branch":[76,98],"that":[77],"generates":[78],"multiple":[79],"sets":[80],"kernels":[82],"adaptively":[84],"fuses":[85],"them":[86],"based":[87],"global":[89,132],"feature":[90,109,138],"statistics;":[91],"(ii)":[93],"lightweight":[95],"channel":[96],"attention":[97],"jointly":[99],"with":[100],"spatially":[102],"adaptive":[103],"branch,":[106],"providing":[107],"channel-spatial":[108],"recalibration":[110],"the":[112,144,164,172,178],"fused":[113],"features.":[114],"Injecting":[115],"MSDA":[116],"modules":[117],"at":[118],"both":[119],"shallow":[120],"deep":[122],"encoder":[123],"stages":[124],"enables":[125],"MSDA-UNet":[126,148],"capture":[128],"local":[129],"details":[130],"semantics":[133],"across":[134],"scales,":[135],"thereby":[136],"improving":[137],"discriminability":[139],"boundary":[141],"precision.":[142],"On":[143],"Synapse":[145],"multi-organ":[146],"benchmark,":[147],"improves":[149],"Dice":[150],"Similarity":[151],"Coefficient":[152],"(DSC)":[153],"by":[154,161],"8.60%":[155],"reduces":[157],"Hausdorff":[158],"Distance":[159],"(HD)":[160],"4.86mm":[162],"over":[163],"baseline":[165],"while":[167],"maintaining":[168],"comparable":[169],"complexity,":[170],"validating":[171],"effectiveness":[173],"practical":[175],"utility":[176],"proposed":[179],"method.":[180]},"counts_by_year":[],"updated_date":"2026-07-13T07:31:44.756512","created_date":"2025-12-23T00:00:00"}