{"id":"https://openalex.org/W7126112367","doi":"https://doi.org/10.1109/bibm66473.2025.11356507","title":"LASGA: Lesion-Aware Saliency-Guided Adversarial Attack for Diabetic Retinopathy Grading","display_name":"LASGA: Lesion-Aware Saliency-Guided Adversarial Attack for Diabetic Retinopathy Grading","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126112367","doi":"https://doi.org/10.1109/bibm66473.2025.11356507"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11356507","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356507","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/A5084061498","display_name":"Yijia Zeng","orcid":"https://orcid.org/0000-0001-7978-8010"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":true,"raw_author_name":"Yijia Zeng","raw_affiliation_strings":["University of Macau"],"affiliations":[{"raw_affiliation_string":"University of Macau","institution_ids":["https://openalex.org/I204512498"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124227094","display_name":"Chi-Man Pun","orcid":null},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Chi-Man Pun","raw_affiliation_strings":["University of Macau"],"affiliations":[{"raw_affiliation_string":"University of Macau","institution_ids":["https://openalex.org/I204512498"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5084061498"],"corresponding_institution_ids":["https://openalex.org/I204512498"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.84112026,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3190","last_page":"3195"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9653000235557556,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9653000235557556,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.00930000003427267,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.0026000000070780516,"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/interpretability","display_name":"Interpretability","score":0.7773000001907349},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6773999929428101},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5490999817848206},{"id":"https://openalex.org/keywords/diabetic-retinopathy","display_name":"Diabetic retinopathy","score":0.4404999911785126},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43689998984336853},{"id":"https://openalex.org/keywords/grading","display_name":"Grading (engineering)","score":0.4163999855518341},{"id":"https://openalex.org/keywords/blindness","display_name":"Blindness","score":0.4138999879360199}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.7773000001907349},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6773999929428101},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6444000005722046},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.630299985408783},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5490999817848206},{"id":"https://openalex.org/C2779829184","wikidata":"https://www.wikidata.org/wiki/Q631361","display_name":"Diabetic retinopathy","level":3,"score":0.4404999911785126},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43689998984336853},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43549999594688416},{"id":"https://openalex.org/C2777286243","wikidata":"https://www.wikidata.org/wiki/Q5591926","display_name":"Grading (engineering)","level":2,"score":0.4163999855518341},{"id":"https://openalex.org/C2780929884","wikidata":"https://www.wikidata.org/wiki/Q737460","display_name":"Blindness","level":2,"score":0.4138999879360199},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.3546999990940094},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28839999437332153},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2858000099658966},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.2847999930381775},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.25459998846054077}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11356507","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356507","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":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7837621569633484}],"awards":[{"id":"https://openalex.org/G3244434723","display_name":null,"funder_award_id":"MYRG-GRG2024-00065-FST-UMDF","funder_id":"https://openalex.org/F4320322841","funder_display_name":"Universidade de Macau"}],"funders":[{"id":"https://openalex.org/F4320315893","display_name":"VNU Science and Technology Development Fund","ror":"https://ror.org/044vr6g03"},{"id":"https://openalex.org/F4320322841","display_name":"Universidade de Macau","ror":"https://ror.org/01r4q9n85"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1969496006","https://openalex.org/W1973190657","https://openalex.org/W2772246530","https://openalex.org/W2828862258","https://openalex.org/W2888424632","https://openalex.org/W2946839276","https://openalex.org/W2963542245","https://openalex.org/W2963857521","https://openalex.org/W2964121744","https://openalex.org/W3085574514","https://openalex.org/W3105377477","https://openalex.org/W3203435379","https://openalex.org/W3204146347","https://openalex.org/W4210530727","https://openalex.org/W4312934823","https://openalex.org/W4328055030","https://openalex.org/W4377966851","https://openalex.org/W4386066653","https://openalex.org/W4386076072","https://openalex.org/W4386697749","https://openalex.org/W4390872600","https://openalex.org/W4391582571","https://openalex.org/W4399355354","https://openalex.org/W4399385464","https://openalex.org/W4403067402","https://openalex.org/W4403649914","https://openalex.org/W4403780797","https://openalex.org/W4408307107","https://openalex.org/W4412455461"],"related_works":[],"abstract_inverted_index":{"Diabetic":[0],"retinopathy":[1],"(DR)":[2],"is":[3],"a":[4,50,66,105],"leading":[5],"cause":[6],"of":[7,41,180],"blindness":[8],"worldwide,":[9],"requiring":[10],"accurate":[11],"lesion":[12,61,75],"classification":[13],"for":[14,93,142,176],"proactive":[15],"intervention.":[16],"While":[17],"deep":[18],"learning":[19],"models":[20,44,156],"have":[21],"improved":[22],"diagnostic":[23],"accuracy,":[24],"their":[25,31],"sensitivity":[26],"to":[27,60,81,87,118],"subtle":[28],"noise":[29],"challenges":[30],"clinical":[32,184],"reliability.":[33],"This":[34],"paper":[35],"examines":[36],"the":[37,137,178],"robustness":[38,132,140],"and":[39,115,133,149,170],"interpretability":[40],"DR":[42,94,143,181],"grading":[43,182],"under":[45],"adversarial":[46,120,139],"attacks.":[47],"We":[48,102],"propose":[49],"novel":[51],"Lesion-Aware":[52],"Saliency-Guided":[53],"Adversarial":[54],"Attack":[55],"(LASGA)":[56],"that":[57,73,111,122,161],"restricts":[58],"perturbations":[59,86],"regions.":[62],"Our":[63],"approach":[64],"introduces":[65],"Lesion-aware":[67],"Saliency":[68],"Map":[69],"Generation":[70],"(LSMG)":[71],"module":[72],"incorporates":[74],"awareness":[76],"into":[77],"static":[78],"saliency":[79],"maps":[80],"guide":[82],"perturbation":[83],"optimization,":[84],"allowing":[85],"focus":[88],"on":[89,154],"key":[90],"regions":[91],"crucial":[92],"decision-making":[95],"while":[96,125],"reducing":[97],"artifacts":[98],"in":[99,167,183],"smooth":[100],"backgrounds.":[101],"also":[103],"design":[104],"Dual":[106],"Strategic":[107],"Perturbation":[108],"Mechanism":[109],"(DSPM)":[110],"combines":[112],"prediction":[113],"loss":[114,117],"consistency":[116],"generate":[119],"examples":[121],"mislead":[123],"diagnosis":[124],"remaining":[126],"imperceptible.":[127],"To":[128],"systematically":[129],"evaluate":[130],"model":[131],"interpretability,":[134],"we":[135],"establish":[136],"first":[138],"benchmark":[141],"grading,":[144],"integrating":[145],"traditional":[146],"attacks,":[147],"LASGA,":[148],"hybrid":[150],"approaches.":[151],"Extensive":[152],"experiments":[153],"four":[155],"across":[157],"three":[158],"datasets":[159],"demonstrate":[160],"our":[162],"method":[163],"outperforms":[164],"baseline":[165],"attacks":[166],"both":[168],"white-box":[169],"black-box":[171],"settings,":[172],"providing":[173],"valuable":[174],"insights":[175],"enhancing":[177],"security":[179],"practice.":[185]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-01-30T00:00:00"}