{"id":"https://openalex.org/W7161744582","doi":"https://doi.org/10.1109/lsp.2026.3694345","title":"DPGNet: Dual Prior Guided Network for Surgical Instrument Segmentation","display_name":"DPGNet: Dual Prior Guided Network for Surgical Instrument Segmentation","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7161744582","doi":"https://doi.org/10.1109/lsp.2026.3694345"},"language":null,"primary_location":{"id":"doi:10.1109/lsp.2026.3694345","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2026.3694345","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-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/A5136466180","display_name":"Jiangpeng Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I9086337","display_name":"Taiyuan University of Technology","ror":"https://ror.org/03kv08d37","country_code":"CN","type":"education","lineage":["https://openalex.org/I9086337"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangpeng Shi","raw_affiliation_strings":["College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, China"],"raw_orcid":"https://orcid.org/0009-0000-4136-4968","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, China","institution_ids":["https://openalex.org/I9086337"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121507618","display_name":"Lina Pang","orcid":null},"institutions":[{"id":"https://openalex.org/I9086337","display_name":"Taiyuan University of Technology","ror":"https://ror.org/03kv08d37","country_code":"CN","type":"education","lineage":["https://openalex.org/I9086337"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lina Pang","raw_affiliation_strings":["College of Software, Taiyuan University of Technology, Taiyuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Software, Taiyuan University of Technology, Taiyuan, China","institution_ids":["https://openalex.org/I9086337"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100358500","display_name":"Jianfeng Wang","orcid":"https://orcid.org/0000-0001-5297-0293"},"institutions":[{"id":"https://openalex.org/I9086337","display_name":"Taiyuan University of Technology","ror":"https://ror.org/03kv08d37","country_code":"CN","type":"education","lineage":["https://openalex.org/I9086337"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianfeng Wang","raw_affiliation_strings":["College of Software, Taiyuan University of Technology, Taiyuan, China"],"raw_orcid":"https://orcid.org/0000-0003-3080-6657","affiliations":[{"raw_affiliation_string":"College of Software, Taiyuan University of Technology, Taiyuan, China","institution_ids":["https://openalex.org/I9086337"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I9086337"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.72257972,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":null,"first_page":"2076","last_page":"2080"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10916","display_name":"Surgical Simulation and Training","score":0.6894000172615051,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10916","display_name":"Surgical Simulation and Training","score":0.6894000172615051,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/T14510","display_name":"Medical Imaging and Analysis","score":0.0560000017285347,"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/T11984","display_name":"Anatomy and Medical Technology","score":0.02500000037252903,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.5727999806404114},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5271999835968018},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4699999988079071},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4115999937057495},{"id":"https://openalex.org/keywords/surgical-instrument","display_name":"Surgical instrument","score":0.4099999964237213},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.32690000534057617},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.31279999017715454}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7184000015258789},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6765000224113464},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6588000059127808},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.5727999806404114},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5271999835968018},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4699999988079071},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4115999937057495},{"id":"https://openalex.org/C2778181360","wikidata":"https://www.wikidata.org/wiki/Q1074814","display_name":"Surgical instrument","level":2,"score":0.4099999964237213},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.32690000534057617},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.31279999017715454},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.31049999594688416},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2955000102519989},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2651999890804291},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.25679999589920044},{"id":"https://openalex.org/C2986158284","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Distance measurement","level":2,"score":0.2517000138759613},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2026.3694345","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2026.3694345","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2542400961","display_name":null,"funder_award_id":"U21A20469","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4307676560","display_name":null,"funder_award_id":"62376183","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8239764594","display_name":null,"funder_award_id":"62476190","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":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Automatic":[0],"surgical":[1],"instrument":[2],"segmentation":[3],"from":[4,50],"endoscopic":[5],"videos":[6],"is":[7,66,103],"essential":[8],"for":[9],"computer-assisted":[10],"intervention.":[11],"However,":[12],"accurately":[13],"segmenting":[14],"instruments":[15],"remains":[16],"challenging":[17],"due":[18],"to":[19,68,105],"occlusion,":[20],"illumination":[21],"variations,":[22],"and":[23,56,76,92,117],"complex":[24],"shapes.":[25],"CNN-":[26],"or":[27],"ViT-based":[28],"methods":[29],"often":[30],"achieve":[31],"limited":[32],"performance.":[33],"To":[34],"address":[35],"this":[36],"issue,":[37],"we":[38],"propose":[39],"a":[40,51,57,63,98],"Dual":[41],"Prior":[42],"Guided":[43,100],"Network":[44],"(DPGNet)":[45],"that":[46,121],"jointly":[47],"exploits":[48],"representations":[49,75],"visual":[52],"foundation":[53],"model":[54,60],"(VFM)":[55],"state":[58],"space":[59],"(SSM).":[61],"Specifically,":[62],"Mamba-Enhanced":[64],"Adapter":[65],"introduced":[67],"bridge":[69],"the":[70,86,115],"gap":[71],"between":[72],"general":[73],"VFM":[74],"instrument-specific":[77],"cues":[78],"through":[79],"multi-scale":[80,107],"feature":[81,94],"modeling.":[82],"This":[83],"design":[84],"ensures":[85],"network":[87],"captures":[88],"fine-grained":[89],"structural":[90],"details":[91],"cross-scale":[93,111],"interactions.":[95],"In":[96],"addition,":[97],"Multi-Context":[99],"(MCG)":[101],"decoder":[102],"designed":[104],"fuse":[106],"encoder":[108],"features":[109],"via":[110],"attention.":[112],"Experiments":[113],"on":[114],"Kvasir-Instrument":[116],"EndoVis2017":[118],"datasets":[119],"demonstrate":[120],"DPGNet":[122,127],"consistently":[123],"outperforms":[124],"existing":[125],"methods.":[126],"code":[128],"will":[129],"be":[130],"available":[131],"at":[132],"<uri":[133],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[134],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://anonymous.4open.science/r/DPGNet-1A44</uri>.":[135]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2026-05-20T00:00:00"}
