{"id":"https://openalex.org/W4409723457","doi":"https://doi.org/10.1109/tmi.2025.3563523","title":"Robust Deep Convolutional Dictionary Model With Alignment Assistance for Multi-Contrast MRI Super-Resolution","display_name":"Robust Deep Convolutional Dictionary Model With Alignment Assistance for Multi-Contrast MRI Super-Resolution","publication_year":2025,"publication_date":"2025-04-23","ids":{"openalex":"https://openalex.org/W4409723457","doi":"https://doi.org/10.1109/tmi.2025.3563523","pmid":"https://pubmed.ncbi.nlm.nih.gov/40266866"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2025.3563523","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2025.3563523","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"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 Medical Imaging","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/A5067046405","display_name":"Pengcheng Lei","orcid":"https://orcid.org/0000-0002-9940-1765"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Pengcheng Lei","raw_affiliation_strings":["School of Computer Science and Technology, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100357903","display_name":"Miaomiao Zhang","orcid":"https://orcid.org/0000-0002-4468-4497"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Miaomiao Zhang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA, USA","Department of Electrical and Computer Engineering, University of Virginia, Virginia, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA, USA","institution_ids":["https://openalex.org/I51556381"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Virginia, Virginia, USA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044588347","display_name":"Faming Fang","orcid":"https://orcid.org/0000-0003-4511-4813"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Faming Fang","raw_affiliation_strings":["School of Computer Science and Technology, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060120202","display_name":"Guixu Zhang","orcid":"https://orcid.org/0000-0003-4720-6607"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guixu Zhang","raw_affiliation_strings":["School of Computer Science and Technology, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5067046405"],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":4.1201,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.93545697,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"44","issue":"8","first_page":"3383","last_page":"3396"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9682000279426575,"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":0.9682000279426575,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.942799985408783,"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"}},{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.9340999722480774,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.711236834526062},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6982641220092773},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.5919190645217896},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5379449129104614},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5347389578819275},{"id":"https://openalex.org/keywords/superresolution","display_name":"Superresolution","score":0.4571854770183563},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4554940164089203},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.44976502656936646},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4174646735191345},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.18047326803207397}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.711236834526062},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6982641220092773},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.5919190645217896},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5379449129104614},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5347389578819275},{"id":"https://openalex.org/C141239990","wikidata":"https://www.wikidata.org/wiki/Q957423","display_name":"Superresolution","level":3,"score":0.4571854770183563},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4554940164089203},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.44976502656936646},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4174646735191345},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18047326803207397}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/tmi.2025.3563523","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2025.3563523","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"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 Medical Imaging","raw_type":"journal-article"},{"id":"pmid:40266866","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40266866","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 medical imaging","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7742197465","display_name":null,"funder_award_id":"2022ZD0161800","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8541016986","display_name":null,"funder_award_id":"62271203","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/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1499310009","https://openalex.org/W1641498739","https://openalex.org/W1901129140","https://openalex.org/W2014934138","https://openalex.org/W2100556411","https://openalex.org/W2134584543","https://openalex.org/W2146842127","https://openalex.org/W2194775991","https://openalex.org/W2677750391","https://openalex.org/W2866634454","https://openalex.org/W2891631795","https://openalex.org/W2895598217","https://openalex.org/W2897421580","https://openalex.org/W2902828227","https://openalex.org/W2949402056","https://openalex.org/W2953427271","https://openalex.org/W2966737464","https://openalex.org/W3014859219","https://openalex.org/W3014974815","https://openalex.org/W3035250394","https://openalex.org/W3037922936","https://openalex.org/W3047142913","https://openalex.org/W3110966546","https://openalex.org/W3161947941","https://openalex.org/W3165579152","https://openalex.org/W3183434090","https://openalex.org/W3193697785","https://openalex.org/W3197279620","https://openalex.org/W3202223141","https://openalex.org/W3207918547","https://openalex.org/W4226497331","https://openalex.org/W4282976788","https://openalex.org/W4285600427","https://openalex.org/W4297847054","https://openalex.org/W4312233661","https://openalex.org/W4323519308","https://openalex.org/W4385764511","https://openalex.org/W4387210992","https://openalex.org/W4387211174","https://openalex.org/W4387211403","https://openalex.org/W4390873327","https://openalex.org/W4390873495","https://openalex.org/W4391524129","https://openalex.org/W4392007289","https://openalex.org/W4396777610","https://openalex.org/W4400905605","https://openalex.org/W4401692222","https://openalex.org/W4402753589","https://openalex.org/W6767423860","https://openalex.org/W6784455011","https://openalex.org/W6795288823"],"related_works":["https://openalex.org/W4389989350","https://openalex.org/W2362774332","https://openalex.org/W4249245269","https://openalex.org/W2765548132","https://openalex.org/W2025681766","https://openalex.org/W2542402767","https://openalex.org/W3023086044","https://openalex.org/W2143529858","https://openalex.org/W2294441925","https://openalex.org/W4367590696"],"abstract_inverted_index":{"Multi-contrast":[0],"magnetic":[1],"resonance":[2],"imaging":[3],"(MCMRI)":[4],"super-resolution":[5],"(SR)":[6],"methods":[7,20,58,250],"aims":[8],"to":[9,29,92,107,140,152,174,195,215],"leverage":[10],"the":[11,32,45,63,143,149,155,159,170,176,180,197,206,209],"complementary":[12,64],"information":[13,65,72,157,193],"present":[14],"in":[15,53,71,130,158,251],"multi-contrast":[16,35,68,87,110,132],"images.":[17,237],"However,":[18],"existing":[19,57,246],"encounter":[21],"several":[22],"limitations.":[23],"Firstly,":[24],"most":[25],"current":[26],"networks":[27],"fail":[28],"appropriately":[30],"model":[31,77,91,101,151,177,223,244],"correlations":[33],"of":[34,48,253],"images":[36,111],"and":[37,74,117,122,178,200,234,257],"lack":[38],"certain":[39],"interpretability.":[40],"Secondly,":[41],"they":[42],"often":[43],"overlook":[44],"negative":[46],"impact":[47],"spatial":[49,128,137],"misalignment":[50],"between":[51,67,208],"modalities":[52],"clinical":[54],"practice.":[55],"Thirdly,":[56],"do":[59],"not":[60],"effectively":[61],"constrain":[62,196],"learned":[66],"images,":[69,133],"resulting":[70],"redundancy":[73,207],"limiting":[75],"their":[76],"performance.":[78,259],"In":[79],"this":[80],"paper,":[81],"we":[82,97,134,190],"propose":[83],"a":[84,136,184],"robust":[85],"alignment-assisted":[86],"convolutional":[88,104,186],"dictionary":[89,187],"(A2-CDic)":[90],"address":[93],"these":[94],"challenges.":[95],"Specifically,":[96],"develop":[98],"an":[99],"observation":[100],"based":[102],"on":[103,224],"sparse":[105],"coding":[106],"explicitly":[108],"represent":[109],"as":[112],"common":[113,199],"(e.g.,":[114,119],"consistent":[115],"textures)":[116],"unique":[118,201],"inconsistent":[120,166],"structures":[121],"contrasts)":[123],"components.":[124,202],"Considering":[125],"there":[126],"are":[127],"misalignments":[129],"real-world":[131],"incorporate":[135],"alignment":[138],"module":[139],"compensate":[141],"for":[142],"misaligned":[144,235],"structures.":[145],"This":[146,203],"approach":[147],"enables":[148],"proposed":[150],"fully":[153],"exploit":[154],"valuable":[156],"reference":[160],"image":[161],"while":[162],"mitigating":[163],"interference":[164],"from":[165],"information.":[167],"We":[168,220],"employ":[169],"proximal":[171],"gradient":[172],"algorithm":[173],"optimize":[175],"unroll":[179],"iterative":[181],"steps":[182],"into":[183],"multi-scale":[185],"network.":[188],"Furthermore,":[189],"utilize":[191],"mutual":[192],"losses":[194],"extracted":[198],"constraint":[204],"reduces":[205],"decomposed":[210],"components,":[211],"allowing":[212],"each":[213],"sub-module":[214],"learn":[216],"more":[217],"representative":[218],"features.":[219],"evaluate":[221],"our":[222,243],"four":[225],"publicly":[226],"available":[227,262],"datasets":[228],"comprising":[229],"internal,":[230],"external,":[231],"spatially":[232],"aligned,":[233],"MCMRI":[236,248],"The":[238],"experimental":[239],"results":[240],"demonstrate":[241],"that":[242],"surpasses":[245],"state-of-the-art":[247],"SR":[249],"terms":[252],"both":[254],"generalization":[255],"ability":[256],"overall":[258],"Code":[260],"is":[261],"at":[263],"https://github.com/lpcccc-cv/A2-CDic.":[264]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-13T16:22:10.518609","created_date":"2025-10-10T00:00:00"}
