{"id":"https://openalex.org/W7135030737","doi":"https://doi.org/10.48550/arxiv.2603.10253","title":"Joint Imaging-ROI Representation Learning via Cross-View Contrastive Alignment for Brain Disorder Classification","display_name":"Joint Imaging-ROI Representation Learning via Cross-View Contrastive Alignment for Brain Disorder Classification","publication_year":2026,"publication_date":"2026-03-10","ids":{"openalex":"https://openalex.org/W7135030737","doi":"https://doi.org/10.48550/arxiv.2603.10253"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.10253","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10253","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.10253","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128815057","display_name":"Wei Liang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128902826","display_name":"Lifang He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Lifang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.4674000144004822,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.4674000144004822,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.36090001463890076,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"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":0.02410000003874302,"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/interpretability","display_name":"Interpretability","score":0.9047999978065491},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.779699981212616},{"id":"https://openalex.org/keywords/complementarity","display_name":"Complementarity (molecular biology)","score":0.6894000172615051},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.6292999982833862},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5985999703407288},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.5149999856948853}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9047999978065491},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.779699981212616},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7027999758720398},{"id":"https://openalex.org/C202269582","wikidata":"https://www.wikidata.org/wiki/Q2644277","display_name":"Complementarity (molecular biology)","level":2,"score":0.6894000172615051},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6524999737739563},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.6292999982833862},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5985999703407288},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.5149999856948853},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4715999960899353},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46790000796318054},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.421099990606308},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4007999897003174},{"id":"https://openalex.org/C58693492","wikidata":"https://www.wikidata.org/wiki/Q551875","display_name":"Neuroimaging","level":2,"score":0.30809998512268066},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.30160000920295715},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.251800000667572}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.10253","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10253","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.10253","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10253","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7429150938987732}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Brain":[0],"imaging":[1],"classification":[2,155],"is":[3,198,210],"commonly":[4],"approached":[5],"from":[6,105,114],"two":[7],"perspectives:":[8],"modeling":[9],"the":[10,106,144,181],"full":[11],"image":[12],"volume":[13],"to":[14,23,109],"capture":[15],"global":[16,84,193],"anatomical":[17],"context,":[18],"or":[19],"constructing":[20],"ROI-based":[21,172],"graphs":[22],"encode":[24],"localized":[25],"and":[26,39,51,86,90,126,133,146,171,195],"topological":[27],"interactions.":[28],"Although":[29],"both":[30],"representations":[31,104,197],"have":[32],"demonstrated":[33],"independent":[34],"efficacy,":[35],"their":[36],"relative":[37],"contributions":[38],"potential":[40],"complementarity":[41],"remain":[42],"insufficiently":[43],"understood.":[44],"Existing":[45],"fusion":[46,125],"approaches":[47],"are":[48],"typically":[49],"task-specific":[50],"do":[52],"not":[53],"enable":[54],"controlled":[55],"evaluation":[56,129],"of":[57,130],"each":[58],"representation":[59,78],"under":[60],"consistent":[61],"training":[62,139],"settings.":[63],"To":[64],"address":[65],"this":[66],"gap,":[67],"we":[68],"propose":[69],"a":[70,94,99,137,199],"unified":[71,138],"cross-view":[72],"contrastive":[73,101],"framework":[74],"for":[75,123,202],"joint":[76,134,151],"imaging-ROI":[77],"learning.":[79],"Our":[80],"method":[81],"learns":[82],"subject-level":[83],"(imaging)":[85],"local":[87],"(ROI-graph)":[88],"embeddings":[89,121],"aligns":[91],"them":[92],"in":[93],"shared":[95],"latent":[96],"space":[97],"using":[98],"bidirectional":[100],"objective,":[102],"encouraging":[103],"same":[107],"subject":[108],"converge":[110],"while":[111],"separating":[112],"those":[113],"different":[115],"subjects.":[116],"This":[117],"alignment":[118],"produces":[119],"comparable":[120],"suitable":[122],"downstream":[124],"enables":[127],"systematic":[128],"imaging-only,":[131],"ROI-only,":[132],"configurations":[135],"within":[136],"protocol.":[140],"Extensive":[141],"experiments":[142],"on":[143],"ADHD-200":[145],"ABIDE":[147],"datasets":[148],"demonstrate":[149],"that":[150,169,190],"learning":[152],"consistently":[153],"improves":[154],"performance":[156,183],"over":[157],"either":[158],"branch":[159],"alone":[160],"across":[161],"multiple":[162],"backbone":[163],"choices.":[164],"Moreover,":[165],"interpretability":[166],"analyses":[167],"reveal":[168],"imaging-based":[170],"branches":[173],"emphasize":[174],"distinct":[175],"yet":[176],"complementary":[177],"discriminative":[178],"patterns,":[179],"explaining":[180],"observed":[182],"gains.":[184],"These":[185],"findings":[186],"provide":[187],"principled":[188],"evidence":[189],"explicitly":[191],"integrating":[192],"volumetric":[194],"ROI-level":[196],"promising":[200],"direction":[201],"neuroimaging-based":[203],"brain":[204],"disorder":[205],"classification.":[206],"The":[207],"source":[208],"code":[209],"available":[211],"at":[212],"https://anonymous.4open.science/r/imaging-roi-contrastive-152C/.":[213]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-13T00:00:00"}