{"id":"https://openalex.org/W7123345161","doi":"https://doi.org/10.1109/tcsvt.2026.3651378","title":"CCDM: Continuous-Time Conditional Diffusion Model for Blind CMRI Super-Resolution","display_name":"CCDM: Continuous-Time Conditional Diffusion Model for Blind CMRI Super-Resolution","publication_year":2026,"publication_date":"2026-01-12","ids":{"openalex":"https://openalex.org/W7123345161","doi":"https://doi.org/10.1109/tcsvt.2026.3651378"},"language":null,"primary_location":{"id":"doi:10.1109/tcsvt.2026.3651378","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2026.3651378","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Circuits and Systems for Video Technology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011606369","display_name":"Defu Qiu","orcid":"https://orcid.org/0000-0003-4921-9145"},"institutions":[{"id":"https://openalex.org/I202126657","display_name":"Qufu Normal University","ror":"https://ror.org/03ceheh96","country_code":"CN","type":"education","lineage":["https://openalex.org/I202126657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Defu Qiu","raw_affiliation_strings":["School of Computer Science, Qufu Normal University, Rizhao, China"],"raw_orcid":"https://orcid.org/0000-0003-4921-9145","affiliations":[{"raw_affiliation_string":"School of Computer Science, Qufu Normal University, Rizhao, China","institution_ids":["https://openalex.org/I202126657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122850029","display_name":"Junliang Shang","orcid":"https://orcid.org/0000-0002-8488-2228"},"institutions":[{"id":"https://openalex.org/I202126657","display_name":"Qufu Normal University","ror":"https://ror.org/03ceheh96","country_code":"CN","type":"education","lineage":["https://openalex.org/I202126657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junliang Shang","raw_affiliation_strings":["School of Computer Science, Qufu Normal University, Rizhao, China"],"raw_orcid":"https://orcid.org/0000-0002-8488-2228","affiliations":[{"raw_affiliation_string":"School of Computer Science, Qufu Normal University, Rizhao, China","institution_ids":["https://openalex.org/I202126657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122886267","display_name":"Yuanke Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I202126657","display_name":"Qufu Normal University","ror":"https://ror.org/03ceheh96","country_code":"CN","type":"education","lineage":["https://openalex.org/I202126657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanke Zhang","raw_affiliation_strings":["School of Computer Science, Qufu Normal University, Rizhao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Qufu Normal University, Rizhao, China","institution_ids":["https://openalex.org/I202126657"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wenjun Zhang","orcid":"https://orcid.org/0000-0001-7973-8769"},"institutions":[{"id":"https://openalex.org/I32625721","display_name":"University of Saskatchewan","ror":"https://ror.org/010x8gc63","country_code":"CA","type":"education","lineage":["https://openalex.org/I32625721"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Wenjun Zhang","raw_affiliation_strings":["Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, SK, Canada"],"raw_orcid":"https://orcid.org/0000-0001-7973-8769","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, SK, Canada","institution_ids":["https://openalex.org/I32625721"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026979934","display_name":"KH Wong","orcid":null},"institutions":[{"id":"https://openalex.org/I32625721","display_name":"University of Saskatchewan","ror":"https://ror.org/010x8gc63","country_code":"CA","type":"education","lineage":["https://openalex.org/I32625721"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Kelvin K. L. Wong","raw_affiliation_strings":["Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, SK, Canada"],"raw_orcid":"https://orcid.org/0000-0002-8600-1105","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, SK, Canada","institution_ids":["https://openalex.org/I32625721"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5122859161","display_name":"Zhang Yi","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhang Yi","raw_affiliation_strings":["Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-5867-9322","affiliations":[{"raw_affiliation_string":"Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04763044,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"36","issue":"5","first_page":"6485","last_page":"6498"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.8003000020980835,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.8003000020980835,"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/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.04610000178217888,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.024800000712275505,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5918999910354614},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49230000376701355},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.47519999742507935},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.41999998688697815},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.40619999170303345},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.37389999628067017},{"id":"https://openalex.org/keywords/conditional-probability-distribution","display_name":"Conditional probability distribution","score":0.35420000553131104},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.3492000102996826},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.3440999984741211},{"id":"https://openalex.org/keywords/importance-sampling","display_name":"Importance sampling","score":0.33869999647140503}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5918999910354614},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.515500009059906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49459999799728394},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49230000376701355},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48350000381469727},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.47519999742507935},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41999998688697815},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4097000062465668},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.40619999170303345},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.37389999628067017},{"id":"https://openalex.org/C43555835","wikidata":"https://www.wikidata.org/wiki/Q2300258","display_name":"Conditional probability distribution","level":2,"score":0.35420000553131104},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3492000102996826},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.3440999984741211},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.33869999647140503},{"id":"https://openalex.org/C21430997","wikidata":"https://www.wikidata.org/wiki/Q5159279","display_name":"Conditional variance","level":4,"score":0.33550000190734863},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.32989999651908875},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3262999951839447},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.31850001215934753},{"id":"https://openalex.org/C143587482","wikidata":"https://www.wikidata.org/wiki/Q1543216","display_name":"Iterative and incremental development","level":2,"score":0.3091999888420105},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.3077000081539154},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.30489999055862427},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.3041999936103821},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.3012999892234802},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.2985999882221222},{"id":"https://openalex.org/C44492722","wikidata":"https://www.wikidata.org/wiki/Q327069","display_name":"Conditional probability","level":2,"score":0.2971999943256378},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.29170000553131104},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.2854999899864197},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.28459998965263367},{"id":"https://openalex.org/C68710425","wikidata":"https://www.wikidata.org/wiki/Q5275442","display_name":"Diffusion process","level":3,"score":0.2784000039100647},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.26179999113082886},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25929999351501465},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.25589999556541443},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.25380000472068787},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsvt.2026.3651378","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2026.3651378","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Circuits and Systems for Video Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7720491886138916,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G3029930106","display_name":null,"funder_award_id":"2025KJH149","funder_id":"https://openalex.org/F4320335428","funder_display_name":"Foundation for Innovative Research Team of Jimei University"},{"id":"https://openalex.org/G4690668261","display_name":null,"funder_award_id":"62472250","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6227921325","display_name":null,"funder_award_id":"62503276","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335428","display_name":"Foundation for Innovative Research Team of Jimei University","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Diffusion":[0],"probabilistic":[1],"models":[2,32],"have":[3],"effectively":[4],"addressed":[5],"the":[6,26,44,50,79,83,89,94,97,114,157],"ill-posed":[7],"nature":[8],"of":[9,49,82,93],"cardiac":[10],"magnetic":[11],"resonance":[12],"imaging":[13],"(CMRI)":[14],"super-resolution":[15],"(SR)":[16],"by":[17,87],"learning":[18],"high-resolution":[19],"image":[20,125,130],"distributions":[21],"from":[22,35],"low-resolution":[23],"inputs.":[24],"However,":[25],"iterative":[27],"sampling":[28],"process":[29],"in":[30,43,96,192],"these":[31,55],"often":[33],"suffers":[34],"slow":[36],"inference":[37],"speeds,":[38],"as":[39,41,108],"well":[40],"limitations":[42],"quality":[45,131,194],"and":[46,91,118,144],"structural":[47],"consistency":[48],"generated":[51],"images.":[52],"To":[53,122],"address":[54],"challenges,":[56],"we":[57,70,101,127,149],"propose":[58,71,128],"a":[59,72,103,109,136,151,162],"continuous-time":[60,73],"conditional":[61,74,158],"diffusion":[62,75,84,183],"model":[63,86],"(CCDM)":[64],"for":[65],"blind":[66],"CMRI":[67,169],"SR.":[68],"Specifically,":[69],"module":[76,133],"that":[77,134,155,179],"reduces":[78],"time":[80,198],"consumption":[81],"probability":[85,172],"maintaining":[88],"mean":[90],"variance":[92],"data":[95],"forward":[98],"process.":[99],"Meanwhile,":[100],"design":[102],"cascaded":[104],"residual":[105],"attention":[106],"network":[107],"feature":[110,119],"extractor":[111],"to":[112,181],"enhance":[113],"model\u2019s":[115],"discriminative":[116],"power":[117],"representation":[120],"capabilities.":[121],"further":[123],"elevate":[124],"fidelity,":[126],"an":[129],"loss":[132],"integrates":[135],"score":[137,153,159],"matching":[138],"loss,":[139],"significantly":[140],"improving":[141],"detail":[142],"reconstruction":[143],"overall":[145],"perceptual":[146],"quality.":[147],"Furthermore,":[148],"develop":[150],"hybrid":[152,163],"predictor":[154],"approximates":[156],"function":[160],"via":[161],"parameterized":[164],"denoising":[165],"network,":[166],"facilitating":[167],"efficient":[168],"generation":[170],"through":[171],"flow":[173],"sampling.":[174],"Extensive":[175],"experimental":[176],"results":[177],"demonstrate":[178],"compared":[180],"existing":[182],"model-based":[184],"SR":[185,193],"methods,":[186],"our":[187],"CCDM":[188],"achieves":[189],"significant":[190],"improvements":[191],"while":[195],"substantially":[196],"reducing":[197],"consumption.":[199]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-01-14T00:00:00"}