{"id":"https://openalex.org/W7163519584","doi":"https://doi.org/10.48550/arxiv.2606.04414","title":"Motion-Guided Causal Disentanglement for Robust Multi-View Cine Cardiac MRI Diagnosis","display_name":"Motion-Guided Causal Disentanglement for Robust Multi-View Cine Cardiac MRI Diagnosis","publication_year":2026,"publication_date":"2026-06-03","ids":{"openalex":"https://openalex.org/W7163519584","doi":"https://doi.org/10.48550/arxiv.2606.04414"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.04414","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04414","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2606.04414","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114173805","display_name":"Chuankai Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Chuankai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133938397","display_name":"Cristiane De Carvalho Singulane","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Singulane, Cristiane De Carvalho","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137851694","display_name":"Mohammad Abuannadi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Abuannadi, Mohammad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137847981","display_name":"Stephen Chandler","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chandler, Stephen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137817052","display_name":"Jeremy Slivnick","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Slivnick, Jeremy","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137862977","display_name":"Karolina Zareba","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zareba, Karolina","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084853615","display_name":"Jane Cao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cao, Jane","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065078721","display_name":"Vidya Nadig","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nadig, Vidya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137907710","display_name":"Fabio Fernandes","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fernandes, Fabio","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034603212","display_name":"Seth Uretsky","orcid":"https://orcid.org/0000-0002-6361-1509"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Uretsky, Seth","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137829577","display_name":"Diego Perez de Arenaza","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"de Arenaza, Diego Perez","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137825006","display_name":"Amit Patel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Patel, Amit","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137867249","display_name":"Jianxin Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Jianxin","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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.18979999423027039,"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"}},"topics":[{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.18979999423027039,"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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.1005999967455864,"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/T10372","display_name":"Cardiac Imaging and Diagnostics","score":0.08810000121593475,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5397999882698059},{"id":"https://openalex.org/keywords/cardiac-imaging","display_name":"Cardiac imaging","score":0.4740999937057495},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.44119998812675476},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.4034000039100647},{"id":"https://openalex.org/keywords/cardiac-magnetic-resonance","display_name":"Cardiac magnetic resonance","score":0.38830000162124634},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.3781999945640564},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.3684000074863434},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.36500000953674316}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5943999886512756},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5794000029563904},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5397999882698059},{"id":"https://openalex.org/C2776127602","wikidata":"https://www.wikidata.org/wiki/Q5038319","display_name":"Cardiac imaging","level":2,"score":0.4740999937057495},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.44119998812675476},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.4034000039100647},{"id":"https://openalex.org/C2987145844","wikidata":"https://www.wikidata.org/wiki/Q5038325","display_name":"Cardiac magnetic resonance","level":3,"score":0.38830000162124634},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3781999945640564},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.3684000074863434},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.36500000953674316},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3637000024318695},{"id":"https://openalex.org/C2776008845","wikidata":"https://www.wikidata.org/wiki/Q5038325","display_name":"Cardiac magnetic resonance imaging","level":3,"score":0.34950000047683716},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.3490999937057495},{"id":"https://openalex.org/C2779974597","wikidata":"https://www.wikidata.org/wiki/Q28448986","display_name":"Clinical Practice","level":2,"score":0.3402000069618225},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.32919999957084656},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.32580000162124634},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.3237999975681305},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30489999055862427},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2655999958515167},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2533999979496002}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.04414","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04414","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2606.04414","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04414","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":0.7142747640609741}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multi-view":[0],"cardiac":[1,67,185],"magnetic":[2],"resonance":[3],"(CMR)":[4],"imaging":[5],"provides":[6],"complementary":[7],"anatomical":[8,40],"information":[9],"and":[10,78,106,114,146,175,184,195],"is":[11,59,138,154],"widely":[12],"used":[13],"for":[14,27,65],"noninvasive":[15],"disease":[16,121,182],"assessment.":[17],"Recent":[18],"transformer-based":[19],"models":[20],"have":[21],"demonstrated":[22],"strong":[23],"representation":[24],"learning":[25,77],"capabilities":[26],"CMR":[28],"analysis;":[29],"however,":[30],"they":[31],"typically":[32],"learn":[33],"unified":[34],"latent":[35,102],"embeddings":[36],"that":[37,119],"entangle":[38],"view-specific":[39,105],"variations":[41],"with":[42],"disease-related":[43],"features.":[44],"Such":[45],"entanglement":[46],"biases":[47],"classifiers":[48],"toward":[49],"structural":[50,208],"attributes":[51],"rather":[52],"than":[53],"view-invariant":[54],"pathological":[55],"patterns.":[56],"This":[57],"issue":[58],"exacerbated":[60],"in":[61,210],"low-data":[62],"regimes,":[63],"particularly":[64],"underrepresented":[66],"conditions,":[68],"where":[69],"limited":[70],"samples":[71],"increase":[72],"the":[73,124,142,157,166,205],"susceptibility":[74],"to":[75,140,160],"shortcut":[76],"view-dependent":[79],"decision":[80],"boundaries.":[81],"To":[82],"address":[83],"this,":[84],"we":[85],"propose":[86],"a":[87,95,115,169],"Motion-Guided":[88],"View--Disease":[89],"Disentanglement":[90],"framework":[91,167],"MoViD":[92],"built":[93],"upon":[94],"ViT-MAE":[96],"backbone.":[97],"The":[98],"model":[99],"explicitly":[100],"factorizes":[101],"representations":[103],"into":[104,123,156],"disease-discriminative":[107],"components":[108],"using":[109],"dual-branch":[110],"supervised":[111],"contrastive":[112,158],"objectives":[113],"gradient-reversal":[116],"adversarial":[117],"constraint":[118],"minimizes":[120],"leakage":[122],"view":[125],"embedding.":[126],"Additionally,":[127],"an":[128],"annotation-free":[129],"temporal":[130],"motion":[131],"feature,":[132],"derived":[133],"from":[134],"inter-frame":[135],"difference":[136],"maps,":[137],"introduced":[139],"localize":[141],"beating":[143],"heart":[144],"region":[145],"suppress":[147],"background":[148],"artifacts.":[149],"A":[150],"focal":[151],"reweighting":[152],"mechanism":[153],"incorporated":[155],"loss":[159],"mitigate":[161],"class":[162],"imbalance.":[163],"We":[164],"evaluate":[165],"on":[168],"private":[170],"clinical":[171],"venous":[172],"thrombosis":[173],"dataset":[174],"two":[176],"public":[177],"benchmarks":[178],"(M&amp;Ms,":[179],"M&amp;Ms2).":[180],"Across":[181],"classification":[183],"segmentation":[186],"tasks,":[187],"our":[188],"approach":[189],"consistently":[190],"outperforms":[191],"standard":[192],"transformer":[193],"baselines":[194],"demonstrates":[196],"competitive":[197],"performance":[198],"against":[199],"large-scale":[200],"pretrained":[201],"foundation":[202],"models,":[203],"validating":[204],"efficacy":[206],"of":[207],"disentanglement":[209],"medical":[211],"image":[212],"analysis.":[213]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-05T00:00:00"}
