{"id":"https://openalex.org/W7141231752","doi":"https://doi.org/10.1109/tip.2026.3673935","title":"Unfolding High-Order Correlations for Interpretable Multi-Contrast MRI Super-Resolution","display_name":"Unfolding High-Order Correlations for Interpretable Multi-Contrast MRI Super-Resolution","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7141231752","doi":"https://doi.org/10.1109/tip.2026.3673935","pmid":"https://pubmed.ncbi.nlm.nih.gov/41894209"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2026.3673935","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3673935","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5045551260","display_name":"Qiangqiang Shen","orcid":"https://orcid.org/0000-0002-3564-6042"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Qiangqiang Shen","raw_affiliation_strings":["Department of Computer Science, City University of Hong Kong, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, City University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082750676","display_name":"Xuanqi Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I153718931","display_name":"University of Ottawa","ror":"https://ror.org/03c4mmv16","country_code":"CA","type":"education","lineage":["https://openalex.org/I153718931"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Xuanqi Zhang","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON, Canada","institution_ids":["https://openalex.org/I153718931"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130796482","display_name":"Peilin Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Peilin Chen","raw_affiliation_strings":["Department of Computer Science, City University of Hong Kong, Hong Kong, China"],"raw_orcid":"https://orcid.org/0000-0001-6636-522X","affiliations":[{"raw_affiliation_string":"Department of Computer Science, City University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100714990","display_name":"Zhiwei Zhong","orcid":"https://orcid.org/0000-0002-7716-8261"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Zhiwei Zhong","raw_affiliation_strings":["Department of Computer Science, City University of Hong Kong, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, City University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001617092","display_name":"Howard Leung","orcid":"https://orcid.org/0000-0002-2633-2965"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Howard Leung","raw_affiliation_strings":["Department of Computer Science, City University of Hong Kong, Hong Kong, China"],"raw_orcid":"https://orcid.org/0000-0002-2633-2965","affiliations":[{"raw_affiliation_string":"Department of Computer Science, City University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5130744304","display_name":"Shiqi Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Shiqi Wang","raw_affiliation_strings":["Department of Computer Science, City University of Hong Kong, Hong Kong, China"],"raw_orcid":"https://orcid.org/0000-0002-3583-959X","affiliations":[{"raw_affiliation_string":"Department of Computer Science, City University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"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":0.30869943,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"35","issue":null,"first_page":"3466","last_page":"3478"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.6432999968528748,"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":0.6432999968528748,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.15839999914169312,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.02199999988079071,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5091999769210815},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.40299999713897705},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.3896999955177307},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.3682999908924103},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.34290000796318054},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.3303999900817871}],"concepts":[{"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/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5091999769210815},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4275999963283539},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.40299999713897705},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.3896999955177307},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3716000020503998},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3682999908924103},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34470000863075256},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.34290000796318054},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.3303999900817871},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.31850001215934753},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.30090001225471497},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2847999930381775},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.2782999873161316},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.25699999928474426},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.2524999976158142}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2026.3673935","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3673935","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},{"id":"pmid:41894209","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41894209","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","id":"https://metadata.un.org/sdg/13","score":0.6075800657272339}],"awards":[{"id":"https://openalex.org/G1025154085","display_name":null,"funder_award_id":"Project N_CityU198/24","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Deep":[0],"unfolding":[1,79],"network":[2,129],"has":[3],"gained":[4],"significant":[5],"attention":[6],"for":[7,92],"magnetic":[8],"resonance":[9],"imaging":[10],"super-resolution":[11],"(MRI":[12],"SR)":[13],"due":[14],"to":[15,65,116,136,149,160,189,221],"its":[16],"performance":[17,216],"and":[18,89,119,122,194],"interpretability.":[19],"However,":[20],"1)":[21],"existing":[22],"methods":[23],"predominantly":[24],"focus":[25],"on":[26,56,104,112,178],"cross-contrast":[27],"correlations":[28,32,140],"while":[29,170],"neglecting":[30],"high-order":[31,139],"embedded":[33],"within":[34],"spatially":[35],"adjacent":[36],"slices":[37],"in":[38],"volumetric":[39],"MRI":[40,81,208],"data.":[41],"2)":[42],"Their":[43],"degradation":[44,101,192],"models":[45],"are":[46],"optimized":[47],"via":[48],"the":[49,105,151,163,179,191,222],"proximal":[50],"gradient":[51,164],"algorithm":[52,188],"(PGA)":[53],"that":[54,211],"relies":[55],"manually":[57],"designed":[58],"hyperparameters":[59],"(e.g.,":[60],"step":[61],"size),":[62],"often":[63],"leading":[64],"overshooting":[66],"or":[67],"suboptimal":[68],"solutions.":[69],"To":[70],"solve":[71,190],"these":[72],"limitations,":[73],"we":[74,96,144,182],"propose":[75],"HocMRI,":[76],"a":[77,99,127,131,146,156,198],"deep":[78,200],"multi-contrast":[80],"SR":[82],"framework,":[83],"which":[84,154],"seamlessly":[85],"integrates":[86],"dual-prior":[87,106],"modeling":[88],"hyperparameter-free":[90,147,180],"PGA":[91,148],"enhanced":[93,218],"reconstruction.":[94],"Specifically,":[95],"first":[97],"design":[98],"novel":[100,132],"model":[102,193],"based":[103,111],"mechanism:":[107],"an":[108,123,184],"explicit":[109],"prior":[110,125],"low-rank":[113],"tensor":[114],"factorization":[115],"capture":[117],"intra-":[118],"inter-slice":[120],"dependencies,":[121],"implicit":[124],"leveraging":[126],"Mamba-based":[128],"with":[130,174,217],"3D":[133],"scanning":[134],"strategy":[135],"further":[137],"exploit":[138],"across":[141],"slices.":[142],"Then,":[143],"derive":[145],"boost":[150],"traditional":[152],"PGA,":[153,181],"employs":[155],"hyperbolic":[157],"tangent":[158],"function":[159],"dynamically":[161],"control":[162],"descent":[165],"step,":[166],"eliminating":[167],"manual":[168],"tuning":[169],"ensuring":[171],"stable":[172],"convergence":[173],"theoretical":[175],"proofs.":[176],"Based":[177],"develop":[183],"efficient":[185],"iterative":[186],"optimization":[187],"unfold":[195],"it":[196],"into":[197],"multi-stage":[199],"network.":[201],"Numerous":[202],"experimental":[203],"results":[204],"from":[205],"widely":[206],"used":[207],"datasets":[209],"demonstrate":[210],"our":[212],"HocMRI":[213],"achieves":[214],"superior":[215],"efficiency":[219],"compared":[220],"state-of-the-art":[223],"methods.":[224]},"counts_by_year":[],"updated_date":"2026-04-04T06:10:10.580331","created_date":"2026-03-28T00:00:00"}
