{"id":"https://openalex.org/W7131436335","doi":"https://doi.org/10.48550/arxiv.2602.19285","title":"MRI Contrast Enhancement Kinetics World Model","display_name":"MRI Contrast Enhancement Kinetics World Model","publication_year":2026,"publication_date":"2026-02-22","ids":{"openalex":"https://openalex.org/W7131436335","doi":"https://doi.org/10.48550/arxiv.2602.19285"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2602.19285","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.19285","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.2602.19285","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126705235","display_name":"Jindi Kong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kong, Jindi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121187475","display_name":"Yuting He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Yuting","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126697891","display_name":"Cong Xia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xia, Cong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124200733","display_name":"Rongjun Ge","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ge, Rongjun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5126837920","display_name":"Shuo Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Shuo","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":0.27239999175071716,"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":0.27239999175071716,"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/T11885","display_name":"MRI in cancer diagnosis","score":0.14159999787807465,"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/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.07010000199079514,"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/overfitting","display_name":"Overfitting","score":0.79339998960495},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.6262999773025513},{"id":"https://openalex.org/keywords/temporal-resolution","display_name":"Temporal resolution","score":0.5163000226020813},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.46880000829696655},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.4489000141620636},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4318999946117401}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.79339998960495},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.6262999773025513},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5809999704360962},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5511000156402588},{"id":"https://openalex.org/C119666444","wikidata":"https://www.wikidata.org/wiki/Q5977280","display_name":"Temporal resolution","level":2,"score":0.5163000226020813},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.46880000829696655},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.4489000141620636},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4318999946117401},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4066999852657318},{"id":"https://openalex.org/C157787499","wikidata":"https://www.wikidata.org/wiki/Q13479657","display_name":"Real-time MRI","level":3,"score":0.37950000166893005},{"id":"https://openalex.org/C41727105","wikidata":"https://www.wikidata.org/wiki/Q17009718","display_name":"Dynamic contrast-enhanced MRI","level":3,"score":0.36000001430511475},{"id":"https://openalex.org/C148898269","wikidata":"https://www.wikidata.org/wiki/Q1108792","display_name":"Kinetics","level":2,"score":0.30239999294281006},{"id":"https://openalex.org/C163985040","wikidata":"https://www.wikidata.org/wiki/Q1172399","display_name":"Data acquisition","level":2,"score":0.2870999872684479},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.2603999972343445},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25760000944137573},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2547000050544739}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2602.19285","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.19285","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.2602.19285","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.19285","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":[{"display_name":"Peace, Justice and strong institutions","score":0.6399568319320679,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Clinical":[0],"MRI":[1,51,129,221],"contrast":[2,34],"acquisition":[3,19,26,52],"suffers":[4],"from":[5],"inefficient":[6],"information":[7],"yield,":[8],"which":[9,196],"presents":[10],"as":[11],"a":[12,61,67,164,186],"mismatch":[13],"between":[14],"the":[15,22,33,38,46,54,72,81,88,103,109,114,124,146,179,183,198,208],"risky":[16],"and":[17,21,24,203,227],"costly":[18],"protocol":[20],"fixed":[23],"sparse":[25],"sequence.":[27],"Applying":[28],"world":[29,57],"models":[30],"to":[31,60,70,75,80,91,93,97,102,112,167,170],"simulate":[32],"enhancement":[35],"kinetics":[36,73,116,184],"in":[37,50,207],"human":[39],"body":[40],"enables":[41],"continuous":[42,106,115],"contrast-free":[43],"dynamics.":[44],"However,":[45],"low":[47],"temporal":[48,107,121,180],"resolution":[49],"restricts":[53],"training":[55,66],"of":[56,83,105],"models,":[58],"leading":[59,96],"sparsely":[62],"sampled":[63],"dataset.":[64],"Directly":[65],"generative":[68],"model":[69,89,110,134],"capture":[71],"leads":[74],"two":[76,217],"limitations:":[77],"(a)":[78],"Due":[79,101],"absence":[82],"data":[84],"on":[85,216],"missing":[86],"time,":[87,119,126],"tends":[90],"overfit":[92],"irrelevant":[94],"features,":[95],"content":[98],"distortion.":[99],"(b)":[100],"lack":[104],"supervision,":[108],"fails":[111],"learn":[113],"law":[117,148,181],"over":[118],"causing":[120],"discontinuities.":[122],"For":[123,142,175],"first":[125],"we":[127,156,190],"propose":[128,157,191],"Contrast":[130],"Enhancement":[131],"Kinetics":[132],"World":[133],"(MRI":[135],"CEKWorld)":[136],"with":[137,172],"SpatioTemporal":[138],"Consistency":[139],"Learning":[140,160,194],"(STCL).":[141],"(a),":[143],"guided":[144,177],"by":[145,178,201],"spatial":[147],"that":[149,162,182],"patient-level":[150],"structures":[151],"remain":[152],"consistent":[153,187],"during":[154],"enhancement,":[155],"Latent":[158,192],"Alignment":[159],"(LAL)":[161],"constructs":[163],"patient-specific":[165],"template":[166],"constrain":[168],"contents":[169,226],"align":[171],"this":[173],"template.":[174],"(b),":[176],"follow":[185],"smooth":[188,205],"trend,":[189],"Difference":[193],"(LDL)":[195],"extends":[197],"unobserved":[199],"intervals":[200],"interpolation":[202],"constrains":[204],"variations":[206],"latent":[209],"space":[210],"among":[211],"interpolated":[212],"sequences.":[213],"Extensive":[214],"experiments":[215],"datasets":[218],"show":[219],"our":[220],"CEKWorld":[222],"achieves":[223],"better":[224],"realistic":[225],"kinetics.":[228],"Codes":[229],"will":[230],"be":[231],"available":[232],"at":[233],"https://github.com/DD0922/MRI-Contrast-Enhancement-Kinetics-World-Model.":[234]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-02-26T00:00:00"}