{"id":"https://openalex.org/W7163014385","doi":"https://doi.org/10.48550/arxiv.2605.31302","title":"MoE-dqINR: A Unified Mixture-of-Experts Implicit Neural Representation Framework for Scan-Specific Dynamic and Quantitative MRI Reconstruction","display_name":"MoE-dqINR: A Unified Mixture-of-Experts Implicit Neural Representation Framework for Scan-Specific Dynamic and Quantitative MRI Reconstruction","publication_year":2026,"publication_date":"2026-05-29","ids":{"openalex":"https://openalex.org/W7163014385","doi":"https://doi.org/10.48550/arxiv.2605.31302"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.31302","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.31302","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.2605.31302","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039464012","display_name":"Yinzhe Wu","orcid":"https://orcid.org/0000-0003-3857-6112"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Yinzhe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011975403","display_name":"Fanwen Wang","orcid":"https://orcid.org/0000-0001-5491-8333"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Fanwen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137593253","display_name":"Zhenxuan Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Zhenxuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137587480","display_name":"Zi Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Zi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137610993","display_name":"Chengyan Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Chengyan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137514558","display_name":"Guang Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Guang","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/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.7074000239372253,"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"}},"topics":[{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.7074000239372253,"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/T10241","display_name":"Functional Brain Connectivity Studies","score":0.0803999975323677,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.04659999907016754,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6202999949455261},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.5680999755859375},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.5551999807357788},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.5034999847412109},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.5016000270843506},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.4544999897480011},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.37299999594688416},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3431999981403351},{"id":"https://openalex.org/keywords/dynamic-contrast-enhanced-mri","display_name":"Dynamic contrast-enhanced MRI","score":0.3422999978065491},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.33809998631477356}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7623999714851379},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6202999949455261},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5791000127792358},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.5680999755859375},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5551999807357788},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.524399995803833},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.5034999847412109},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.5016000270843506},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.4544999897480011},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.37299999594688416},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3431999981403351},{"id":"https://openalex.org/C41727105","wikidata":"https://www.wikidata.org/wiki/Q17009718","display_name":"Dynamic contrast-enhanced MRI","level":3,"score":0.3422999978065491},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.33809998631477356},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.3370000123977661},{"id":"https://openalex.org/C128840427","wikidata":"https://www.wikidata.org/wiki/Q1302174","display_name":"Motion compensation","level":2,"score":0.32760000228881836},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.31949999928474426},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.3127000033855438},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.3034000098705292},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.30149999260902405},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2953999936580658},{"id":"https://openalex.org/C2779226451","wikidata":"https://www.wikidata.org/wiki/Q903809","display_name":"Functional magnetic resonance imaging","level":2,"score":0.2939000129699707},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.28949999809265137},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C163985040","wikidata":"https://www.wikidata.org/wiki/Q1172399","display_name":"Data acquisition","level":2,"score":0.27880001068115234},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2678000032901764},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.26109999418258667},{"id":"https://openalex.org/C37404715","wikidata":"https://www.wikidata.org/wiki/Q380679","display_name":"Dynamic programming","level":2,"score":0.25929999351501465},{"id":"https://openalex.org/C157787499","wikidata":"https://www.wikidata.org/wiki/Q13479657","display_name":"Real-time MRI","level":3,"score":0.2578999996185303},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2565000057220459},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.25619998574256897},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.2524999976158142}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.31302","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.31302","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.2605.31302","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.31302","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Undersampled":[0],"magnetic":[1],"resonance":[2],"imaging":[3],"(MRI)":[4],"reconstruction":[5,99,211],"seeks":[6],"to":[7,88,146,157,190],"recover":[8],"temporally":[9],"or":[10,44,49,134],"contrast-varying":[11],"image":[12,66,120],"series":[13],"from":[14,137,171],"incomplete":[15],"multicoil":[16,97,148,209],"k-space":[17],"data":[18],"while":[19,64,185],"preserving":[20],"state-dependent":[21,172],"fidelity":[22],"for":[23,180],"dynamic":[24,132,162,181],"and":[25,110,163,182,219,222],"quantitative":[26,51,164,183],"MRI":[27,98,149,184,210],"(qMRI).":[28],"Existing":[29],"scan-specific":[30,96,187,208],"implicit":[31],"neural":[32],"representations":[33],"(INRs)":[34],"often":[35],"use":[36],"monolithic":[37],"spatiotemporal":[38],"coordinate":[39],"fields,":[40],"explicit":[41],"subspaces,":[42],"motion":[43],"deformation":[45],"models,":[46],"calibration":[47],"variables,":[48],"sequence-specific":[50],"signal":[52],"models.":[53],"These":[54],"design":[55],"choices":[56],"can":[57],"limit":[58],"flexibility":[59],"in":[60,160,196],"sharing":[61],"spatial":[62,108,169,216],"information":[63],"adapting":[65],"synthesis":[67],"across":[68],"acquisition":[69,128],"states.":[70],"Moreover,":[71],"many":[72],"INR-based":[73],"baselines":[74],"remain":[75],"computationally":[76],"demanding,":[77],"typically":[78],"requiring":[79],"per-scan":[80,224],"optimization":[81,189],"times":[82],"on":[83,126],"the":[84,103,153,174],"order":[85],"of":[86,90],"hundreds":[87],"thousands":[89],"seconds.":[91],"We":[92],"propose":[93],"MoE-dqINR,":[94],"a":[95,111,138,147,207],"framework":[100,175],"that":[101,213],"factorizes":[102],"image-domain":[104],"representation":[105,143,170],"into":[106],"shared":[107,168,215],"experts":[109,116],"state-conditioned":[112,203],"routing":[113,123,159],"pathway.":[114],"Spatial":[115],"encode":[117],"reusable":[118],"coordinate-dependent":[119],"content,":[121],"whereas":[122],"weights,":[124],"conditioned":[125],"ordered":[127],"states,":[129],"synthesize":[130],"each":[131],"frame":[133],"contrast":[135],"state":[136,155],"common":[139],"expert":[140],"bank.":[141],"The":[142,199],"is":[144],"coupled":[145],"forward":[150],"model,":[151],"uses":[152],"normalized":[154],"index":[156],"drive":[158],"both":[161],"MRI.":[165],"By":[166],"separating":[167],"synthesis,":[173,221],"provides":[176],"an":[177],"image-first":[178],"architecture":[179],"reducing":[186],"INR":[188,205],"approximately":[191],"30":[192],"s":[193],"per":[194],"scan":[195],"our":[197],"experiments.":[198],"proposed":[200],"formulation":[201],"establishes":[202],"mixture-of-experts":[204],"as":[206],"prior":[212],"unifies":[214],"representation,":[217],"dynamic-":[218],"qMRI-specific":[220],"practical":[223],"efficiency.":[225]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-02T00:00:00"}
