{"id":"https://openalex.org/W7126078629","doi":"https://doi.org/10.1109/bibm66473.2025.11356152","title":"An End-to-End Dual-View Architecture for Spatial Clustering of Spatial Transcriptomics Data by Integrating Histology Images","display_name":"An End-to-End Dual-View Architecture for Spatial Clustering of Spatial Transcriptomics Data by Integrating Histology Images","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126078629","doi":"https://doi.org/10.1109/bibm66473.2025.11356152"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11356152","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356152","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/A5124167829","display_name":"Xinru Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I202126657","display_name":"Qufu Normal University","ror":"https://ror.org/03ceheh96","country_code":"CN","type":"education","lineage":["https://openalex.org/I202126657"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xinru Xu","raw_affiliation_strings":["The School of Computer Science, Qufu Normal University,Rizhao,Shandong,China"],"affiliations":[{"raw_affiliation_string":"The School of Computer Science, Qufu Normal University,Rizhao,Shandong,China","institution_ids":["https://openalex.org/I202126657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124186599","display_name":"Shengjun Li","orcid":null},"institutions":[{"id":"https://openalex.org/I202126657","display_name":"Qufu Normal University","ror":"https://ror.org/03ceheh96","country_code":"CN","type":"education","lineage":["https://openalex.org/I202126657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengjun Li","raw_affiliation_strings":["The School of Computer Science, Qufu Normal University,Rizhao,Shandong,China"],"affiliations":[{"raw_affiliation_string":"The School of Computer Science, Qufu Normal University,Rizhao,Shandong,China","institution_ids":["https://openalex.org/I202126657"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124226937","display_name":"Juan Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I202126657","display_name":"Qufu Normal University","ror":"https://ror.org/03ceheh96","country_code":"CN","type":"education","lineage":["https://openalex.org/I202126657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Juan Wang","raw_affiliation_strings":["The School of Computer Science and Rizhao-Qufu Normal University, Joint Technology Transfer Center, Qufu Normal University,Rizhao,Shandong,China"],"affiliations":[{"raw_affiliation_string":"The School of Computer Science and Rizhao-Qufu Normal University, Joint Technology Transfer Center, Qufu Normal University,Rizhao,Shandong,China","institution_ids":["https://openalex.org/I202126657"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5124167829"],"corresponding_institution_ids":["https://openalex.org/I202126657"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.65195213,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6392","last_page":"6399"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12859","display_name":"Cell Image Analysis Techniques","score":0.0013000000035390258,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.0006000000284984708,"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/cluster-analysis","display_name":"Cluster analysis","score":0.7422000169754028},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5562000274658203},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.5552999973297119},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5080999732017517},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.49540001153945923},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4018999934196472},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.37450000643730164},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.3589000105857849}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7491000294685364},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7422000169754028},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6843000054359436},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5562000274658203},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.5552999973297119},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5080999732017517},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.49540001153945923},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4018999934196472},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39570000767707825},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3792000114917755},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.37450000643730164},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3589000105857849},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3578000068664551},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.33970001339912415},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3393999934196472},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.33309999108314514},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.32710000872612},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3221000134944916},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.3012000024318695},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2842000126838684},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2815999984741211},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.2669999897480011}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11356152","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356152","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/G1659441718","display_name":null,"funder_award_id":"62172253","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2089468765","https://openalex.org/W2123491442","https://openalex.org/W2558580397","https://openalex.org/W2800392236","https://openalex.org/W3021920958","https://openalex.org/W3033415403","https://openalex.org/W3099810371","https://openalex.org/W3108118546","https://openalex.org/W4290154117","https://openalex.org/W4322387795","https://openalex.org/W4384665375","https://openalex.org/W4394870160","https://openalex.org/W4395073772","https://openalex.org/W4402492182","https://openalex.org/W4409190914","https://openalex.org/W4410339469","https://openalex.org/W4413407448"],"related_works":[],"abstract_inverted_index":{"Spatial":[0],"transcriptomics":[1,28],"(ST)":[2],"technologies":[3],"offer":[4],"an":[5,60,75],"unprecedented":[6],"opportunity":[7],"to":[8,88],"resolve":[9],"complex":[10],"tissue":[11],"microenvironments.":[12],"The":[13,151],"accurate":[14],"identification":[15],"of":[16],"spatial":[17,27,38,69,165],"domains":[18],"is":[19],"still":[20],"a":[21,105],"pivotal":[22],"and":[23,50,71,139,167],"challenging":[24],"task":[25],"in":[26,115,161],"studies.":[29],"Although":[30],"numerous":[31],"computational":[32],"methods":[33,42,159],"have":[34],"been":[35],"developed":[36],"for":[37,113],"domain":[39],"detection,":[40],"prevailing":[41],"struggle":[43],"with":[44,74],"multi-modal":[45],"data":[46,117],"fusion,":[47],"noise":[48,114],"robustness,":[49],"clustering":[51,146,166],"stability.":[52],"To":[53],"address":[54],"these":[55],"limitations,":[56],"we":[57,125],"introduce":[58],"DPST,":[59],"end-to-end":[61],"deep":[62,144],"learning":[63],"model,":[64],"which":[65],"integrates":[66],"gene":[67],"expression,":[68],"coordinates,":[70],"histology":[72,94],"images":[73,95],"attention":[76],"mechanism.":[77,132],"DPST":[78,103,156],"leverages":[79],"the":[80,127,129],"self-supervised":[81],"bootstrap":[82],"your":[83],"own":[84],"latent":[85],"(BYOL)":[86],"framework":[87],"extract":[89],"robust":[90],"feature":[91],"embeddings":[92],"from":[93,121],"without":[96],"requiring":[97],"negative":[98],"samples.":[99],"At":[100],"its":[101],"core,":[102],"employs":[104],"MASK-REMASK":[106],"dual-view":[107],"decoding":[108],"strategy":[109],"that":[110,155],"simultaneously":[111],"corrects":[112],"masked":[116],"while":[118],"recovering":[119],"details":[120],"unmasked":[122],"data.":[123],"Furthermore,":[124],"use":[126],"breaking":[128],"reclustering":[130],"barriers":[131],"This":[133],"mechanism":[134],"incorporates":[135],"weight":[136],"resets,":[137],"reclustering,":[138],"momentum":[140],"resets.":[141],"It":[142],"helps":[143],"embedded":[145],"algorithms":[147],"overcome":[148],"performance":[149],"bottlenecks.":[150],"experimental":[152],"results":[153],"show":[154],"outperforms":[157],"state-of-the-art":[158],"consistently":[160],"several":[162],"tasks,":[163],"including":[164],"trajectory":[168],"inference.":[169]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-01-30T00:00:00"}
