{"id":"https://openalex.org/W7126071120","doi":"https://doi.org/10.1109/bibm66473.2025.11356618","title":"Graph Interaction Prompt Network for Few-Shot Medical Image Anomaly Detection","display_name":"Graph Interaction Prompt Network for Few-Shot Medical Image Anomaly Detection","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126071120","doi":"https://doi.org/10.1109/bibm66473.2025.11356618"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11356618","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356618","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 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/A5100390145","display_name":"Zhen Zhang","orcid":"https://orcid.org/0000-0001-8448-5663"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhongyu Zhang","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology,Nanjing,China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology,Nanjing,China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072705483","display_name":"Fei Tao","orcid":"https://orcid.org/0000-0002-9020-0633"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fenfang Tao","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology,Nanjing,China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology,Nanjing,China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124185942","display_name":"Tianzhu Xiang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210117836","display_name":"Space Micro (United States)","ror":"https://ror.org/03bc0qh53","country_code":"US","type":"company","lineage":["https://openalex.org/I4210117836"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tianzhu Xiang","raw_affiliation_strings":["Space42,United Arab Emirates"],"affiliations":[{"raw_affiliation_string":"Space42,United Arab Emirates","institution_ids":["https://openalex.org/I4210117836"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100329780","display_name":"Fang Zhao","orcid":"https://orcid.org/0000-0002-6772-8042"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fang Zhao","raw_affiliation_strings":["School of Intelligence Science and Technology, Nanjing University,Nanjing,China"],"affiliations":[{"raw_affiliation_string":"School of Intelligence Science and Technology, Nanjing University,Nanjing,China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084688255","display_name":"Guo-Sen Xie","orcid":"https://orcid.org/0000-0002-5487-9845"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guo-Sen Xie","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology,Nanjing,China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology,Nanjing,China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100390145"],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.84069781,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1435","last_page":"1442"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.8191999793052673,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.8191999793052673,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.055399999022483826,"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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.030799999833106995,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/anomaly-detection","display_name":"Anomaly detection","score":0.7052000164985657},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5611000061035156},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.47519999742507935},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.45829999446868896},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4489000141620636},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40209999680519104}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.713100016117096},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7052000164985657},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5611000061035156},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5307999849319458},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.47519999742507935},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.45829999446868896},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4489000141620636},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40209999680519104},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.3458999991416931},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3240000009536743},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3140999972820282},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30649998784065247},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.26409998536109924},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.25589999556541443},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2549999952316284}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11356618","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356618","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2439294401","display_name":null,"funder_award_id":"BK20242015","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G6648088228","display_name":null,"funder_award_id":"62276134,62476124","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"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2295107390","https://openalex.org/W2765793020","https://openalex.org/W2962858109","https://openalex.org/W2963091558","https://openalex.org/W2963466845","https://openalex.org/W2991372685","https://openalex.org/W3034328552","https://openalex.org/W3035253074","https://openalex.org/W3106848223","https://openalex.org/W3166166117","https://openalex.org/W3169024950","https://openalex.org/W3169651898","https://openalex.org/W3195516695","https://openalex.org/W4292851291","https://openalex.org/W4312298392","https://openalex.org/W4385573131","https://openalex.org/W4386065385","https://openalex.org/W4386065890","https://openalex.org/W4386071635","https://openalex.org/W4402703054","https://openalex.org/W4402961681","https://openalex.org/W4403069355","https://openalex.org/W4403420280","https://openalex.org/W4403780904","https://openalex.org/W4404420613","https://openalex.org/W4409366876"],"related_works":[],"abstract_inverted_index":{"Few-shot":[0],"medical":[1,97,168,179],"image":[2],"anomaly":[3,94,156,169,180],"detection":[4,95,181],"aims":[5],"to":[6,122],"detect":[7],"and":[8,39,50,89,128],"locate":[9],"anomalies":[10],"with":[11,146],"limited":[12],"data,":[13],"playing":[14],"a":[15,35,83,102,115,135],"crucial":[16],"role":[17],"in":[18,68,96,114],"clinical":[19],"practice.":[20],"In":[21],"recent":[22],"years,":[23],"the":[24,53,69,77,120,141,147,159,175],"large":[25],"pre-trained":[26],"vision-language":[27,149],"model":[28,121],"CLIP":[29,44],"has":[30],"demonstrated":[31],"impressive":[32],"performance":[33],"across":[34],"variety":[36],"of":[37,55,161],"few-shot":[38,178],"zero-shot":[40],"downstream":[41],"tasks.":[42],"However,":[43],"mainly":[45],"focuses":[46],"on":[47,124,166],"aligning":[48],"text":[49,162],"images,":[51],"emphasizing":[52],"semantics":[54],"global":[56],"foreground":[57],"objects":[58],"rather":[59],"than":[60],"distinguishing":[61],"local":[62],"subtle":[63],"normal":[64],"or":[65],"abnormal":[66],"areas":[67],"images.":[70,98],"To":[71],"address":[72],"this":[73],"challenge,":[74],"we":[75,100,133],"propose":[76],"Graph":[78],"Interaction":[79],"Prompt":[80],"Network":[81],"(GIPN),":[82],"framework":[84],"that":[85,107,172],"leverages":[86],"graph":[87,103,117,143],"interaction":[88,104,144],"text-prompt":[90],"learning":[91],"for":[92,155],"precise":[93],"Specifically,":[99],"introduce":[101],"prompt":[105],"module":[106],"enables":[108],"cross-layer":[109],"interactions":[110],"among":[111],"visual":[112],"features":[113,145],"latent":[116],"space,":[118],"guiding":[119],"focus":[123],"challenging":[125],"anomalous":[126],"regions":[127],"enhancing":[129],"feature":[130],"representations.":[131],"Additionally,":[132],"develop":[134],"dual-stream":[136],"fusion":[137],"strategy,":[138],"which":[139],"merges":[140],"hierarchical":[142],"original":[148],"features,":[150],"better":[151],"capturing":[152],"critical":[153],"cues":[154],"prediction":[157],"under":[158],"guidance":[160],"prompts.":[163],"Extensive":[164],"experiments":[165],"three":[167],"datasets":[170],"demonstrate":[171],"GIPN":[173],"outperforms":[174],"current":[176],"state-of-the-art":[177],"approaches.":[182],"Our":[183],"code":[184],"is":[185],"available":[186],"at":[187],"https://github.com/CVL-hub/GIPN.":[188]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-01-30T00:00:00"}
