{"id":"https://openalex.org/W7138015694","doi":"https://doi.org/10.1609/aaai.v40i5.37395","title":"Zero-shot Implicit Neural Manifold Representation (INMR) for Ultra-high Temporal Resolution Dynamic MRI","display_name":"Zero-shot Implicit Neural Manifold Representation (INMR) for Ultra-high Temporal Resolution Dynamic MRI","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138015694","doi":"https://doi.org/10.1609/aaai.v40i5.37395"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i5.37395","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i5.37395","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v40i5.37395","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129679719","display_name":"Jie Feng","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jie Feng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129742863","display_name":"Rui Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rui Luo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006680031","display_name":"Tian Zeng","orcid":"https://orcid.org/0000-0001-5957-3442"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tian Zeng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100624454","display_name":"Xin Shen","orcid":"https://orcid.org/0009-0006-2699-3292"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xin Shen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129666808","display_name":"Haikun Qi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haikun Qi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129718662","display_name":"Yuyao Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuyao Zhang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129643657","display_name":"Dong Liang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong Liang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129710555","display_name":"Hongjiang Wei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hongjiang Wei","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5129679719"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23702515,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"5","first_page":"3930","last_page":"3938"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.1518000066280365,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.1518000066280365,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.11670000106096268,"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/T12552","display_name":"Fetal and Pediatric Neurological Disorders","score":0.11219999939203262,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"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/temporal-resolution","display_name":"Temporal resolution","score":0.718999981880188},{"id":"https://openalex.org/keywords/dynamic-contrast-enhanced-mri","display_name":"Dynamic contrast-enhanced MRI","score":0.5799000263214111},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5669000148773193},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.548799991607666},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5169000029563904},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4726000130176544},{"id":"https://openalex.org/keywords/real-time-mri","display_name":"Real-time MRI","score":0.435699999332428},{"id":"https://openalex.org/keywords/manifold","display_name":"Manifold (fluid mechanics)","score":0.41029998660087585},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.39809998869895935}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7278000116348267},{"id":"https://openalex.org/C119666444","wikidata":"https://www.wikidata.org/wiki/Q5977280","display_name":"Temporal resolution","level":2,"score":0.718999981880188},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7168999910354614},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.597000002861023},{"id":"https://openalex.org/C41727105","wikidata":"https://www.wikidata.org/wiki/Q17009718","display_name":"Dynamic contrast-enhanced MRI","level":3,"score":0.5799000263214111},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5669000148773193},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.548799991607666},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5169000029563904},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4726000130176544},{"id":"https://openalex.org/C157787499","wikidata":"https://www.wikidata.org/wiki/Q13479657","display_name":"Real-time MRI","level":3,"score":0.435699999332428},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.41029998660087585},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.39809998869895935},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.3962000012397766},{"id":"https://openalex.org/C197301865","wikidata":"https://www.wikidata.org/wiki/Q5318983","display_name":"Dynamic imaging","level":5,"score":0.38359999656677246},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.3824000060558319},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.3596999943256378},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.35910001397132874},{"id":"https://openalex.org/C2779226451","wikidata":"https://www.wikidata.org/wiki/Q903809","display_name":"Functional magnetic resonance imaging","level":2,"score":0.3411000072956085},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.3303000032901764},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.32910001277923584},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.31459999084472656},{"id":"https://openalex.org/C172849965","wikidata":"https://www.wikidata.org/wiki/Q3148875","display_name":"Reference frame","level":3,"score":0.30300000309944153},{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.29499998688697815},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.288100004196167},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.2671000063419342},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.2572000026702881}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i5.37395","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i5.37395","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i5.37395","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i5.37395","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"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":{"Capturing":[0],"accurate":[1],"dynamic":[2,29,58],"information":[3],"of":[4,21,56,156],"moving":[5],"organs":[6],"is":[7],"essential":[8],"for":[9,71,80,169],"functional":[10],"assessment":[11],"using":[12],"non-invasive":[13],"imaging":[14,32,129],"modalities.":[15],"Achieving":[16],"high":[17],"temporal":[18,63,173,180],"resolution":[19,174],"visualization":[20,155],"physiological":[22],"processes":[23],"remains":[24],"a":[25,113],"critical":[26],"challenge":[27],"in":[28,94],"magnetic":[30],"resonance":[31],"(MRI)":[33],"when":[34],"reconstructing":[35,57],"from":[36,98],"extremely":[37],"limited":[38],"acquisitions.":[39],"We":[40],"introduce":[41],"an":[42],"unsupervised":[43],"zero-shot":[44],"reconstruction":[45],"framework":[46,84],"combining":[47],"Implicit":[48],"Neural":[49],"Representation":[50],"(INR)":[51],"with":[52],"manifold":[53,88],"learning,":[54],"capable":[55],"MRI":[59],"data":[60],"at":[61],"unprecedented":[62],"resolutions":[64],"(less":[65],"than":[66,75],"10":[67],"ms":[68,77],"per":[69,78],"frame":[70,79],"2D":[72],"imaging,":[73],"less":[74],"400":[76],"3D":[81],"imaging).":[82],"The":[83,149],"employs":[85],"learnable":[86],"low-dimensional":[87],"vectors":[89],"to":[90,107],"autonomously":[91],"capture":[92],"motion":[93,144,157],"real":[95],"time":[96],"directly":[97],"undersampled":[99],"data,":[100],"and":[101,134,146,158,179],"dynamically":[102],"condition":[103],"coordinate-based":[104],"spatial":[105],"representations":[106],"generate":[108],"high-fidelity":[109],"image":[110],"sequences.":[111],"Through":[112],"novel":[114],"spatiotemporal":[115],"coarse-to-fine":[116],"(C2F)":[117],"optimization":[118],"strategy,":[119],"our":[120],"method":[121],"outperforms":[122],"current":[123],"state-of-the-art":[124],"(SOTA)":[125],"techniques":[126],"across":[127],"multiple":[128],"scenarios,":[130],"including":[131],"cardiac,":[132],"speech":[133],"dynamic-contrast-enhanced":[135],"(DCE)":[136],"abdominal":[137],"MRI,":[138],"demonstrating":[139],"robust":[140],"performance":[141],"under":[142],"challenging":[143],"patterns":[145],"contrast":[147,159],"dynamics.":[148],"learned":[150],"manifolds":[151],"additionally":[152],"provide":[153],"intuitive":[154],"evolution":[160],"during":[161],"imaging.":[162],"These":[163],"advances":[164],"indicate":[165],"strong":[166],"clinical":[167],"potential":[168],"applications":[170],"requiring":[171],"extreme":[172],"while":[175],"maintaining":[176],"both":[177],"anatomical":[178],"fidelity.":[181]},"counts_by_year":[],"updated_date":"2026-03-18T06:31:55.123368","created_date":"2026-03-18T00:00:00"}