{"id":"https://openalex.org/W7116937411","doi":"https://doi.org/10.1109/jbhi.2025.3647429","title":"Re-Visible Dual-Domain Self-Supervised Deep Unfolding Network for MRI Reconstruction","display_name":"Re-Visible Dual-Domain Self-Supervised Deep Unfolding Network for MRI Reconstruction","publication_year":2025,"publication_date":"2025-12-23","ids":{"openalex":"https://openalex.org/W7116937411","doi":"https://doi.org/10.1109/jbhi.2025.3647429","pmid":"https://pubmed.ncbi.nlm.nih.gov/41433179"},"language":"en","primary_location":{"id":"doi:10.1109/jbhi.2025.3647429","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2025.3647429","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"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 Journal of Biomedical and Health Informatics","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/A5121098371","display_name":"Hao Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Zhang","raw_affiliation_strings":["Department of Mathematics, School of Science, Shanghai University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, School of Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121070457","display_name":"Qi Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Wang","raw_affiliation_strings":["Department of Mathematics, School of Science, Shanghai University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0001-2846-3731","affiliations":[{"raw_affiliation_string":"Department of Mathematics, School of Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jian Sun","orcid":"https://orcid.org/0000-0001-7206-0641"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Sun","raw_affiliation_strings":["School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, Shaanxi, China"],"raw_orcid":"https://orcid.org/0000-0001-7206-0641","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, Shaanxi, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121070433","display_name":"Zhijie Wen","orcid":null},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhijie Wen","raw_affiliation_strings":["Department of Mathematics, School of Science, Shanghai University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-8514-1993","affiliations":[{"raw_affiliation_string":"Department of Mathematics, School of Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jun Shi","orcid":"https://orcid.org/0000-0002-3226-3978"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Shi","raw_affiliation_strings":["School of Communication and Information Engineering, Shanghai University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-3226-3978","affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063863772","display_name":"Shihui Ying","orcid":"https://orcid.org/0000-0001-9423-0146"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shihui Ying","raw_affiliation_strings":["Shanghai Institute of Applied Mathematics and Mechanics, Shanghai University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-9423-0146","affiliations":[{"raw_affiliation_string":"Shanghai Institute of Applied Mathematics and Mechanics, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]}],"institutions":[],"countries_distinct_count":1,"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":0.61128443,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"30","issue":"7","first_page":"6147","last_page":"6160"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9399999976158142,"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"}},"topics":[{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9399999976158142,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.00800000037997961,"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/T10241","display_name":"Functional Brain Connectivity Studies","score":0.007300000172108412,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6403999924659729},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6172999739646912},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5892000198364258},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.545199990272522},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.5328999757766724},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47620001435279846},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.46619999408721924},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4587000012397766},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4487999975681305}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8021000027656555},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7354000210762024},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6403999924659729},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6172999739646912},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5892000198364258},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.545199990272522},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5328999757766724},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47620001435279846},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.46619999408721924},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4587000012397766},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4487999975681305},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4016000032424927},{"id":"https://openalex.org/C163985040","wikidata":"https://www.wikidata.org/wiki/Q1172399","display_name":"Data acquisition","level":2,"score":0.3952000141143799},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3950999975204468},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.38179999589920044},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36719998717308044},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.365200012922287},{"id":"https://openalex.org/C118317068","wikidata":"https://www.wikidata.org/wiki/Q2100760","display_name":"Point distribution model","level":2,"score":0.329800009727478},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.32839998602867126},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31139999628067017},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.30390000343322754},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30300000309944153},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.28110000491142273},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2660999894142151},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.26159998774528503},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.258899986743927}],"mesh":[{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine 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":"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":"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}],"locations_count":2,"locations":[{"id":"doi:10.1109/jbhi.2025.3647429","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2025.3647429","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"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 Journal of Biomedical and Health Informatics","raw_type":"journal-article"},{"id":"pmid:41433179","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41433179","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 journal of biomedical and health informatics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4725712073","display_name":null,"funder_award_id":"12571566","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":{"Magnetic":[0],"Resonance":[1],"Imaging":[2],"(MRI)":[3],"is":[4],"widely":[5],"used":[6],"in":[7,38,241],"clinical":[8],"practice,":[9],"but":[10,70],"suffers":[11],"from":[12,66],"prolonged":[13],"acquisition":[14,25],"time.":[15],"Although":[16],"deep":[17,126],"learning":[18,65],"methods":[19,59,73],"have":[20,104],"been":[21],"proposed":[22],"to":[23,112,129,153,168,171,194,206,223],"accelerate":[24],"and":[26,47,97,188,210,231,246],"demonstrate":[27,234],"promising":[28],"performance,":[29],"they":[30],"rely":[31,74],"on":[32,75,186,228],"high-quality":[33],"fully-sampled":[34],"datasets":[35,44,136,233],"for":[36,84],"training":[37,95,152],"a":[39,121,181,200],"supervised":[40],"manner.":[41],"However,":[42],"such":[43],"are":[45,137,149],"time-consuming":[46],"expensive-to-collect,":[48],"which":[49,86],"constrains":[50],"their":[51,102],"broader":[52],"applications.":[53],"On":[54],"the":[55,93,94,98,155,166,213],"other":[56],"hand,":[57],"self-supervised":[58,125],"offer":[60],"an":[61,88],"alternative":[62],"by":[63,140,160],"enabling":[64],"under-sampled":[67,78,135,146,173],"data":[68,80,148,175],"alone,":[69],"most":[71],"existing":[72],"further":[76,161],"partitioned":[77],"k-space":[79,147,174],"as":[81,176],"model's":[82],"input":[83,89,156],"training,":[85],"causes":[87],"distribution":[90,157],"shift":[91,158],"between":[92],"stage":[96],"inference":[99],"stage.":[100],"Additionally,":[101,178],"models":[103],"not":[105],"effectively":[106,215],"incorporated":[107],"comprehensive":[108,220],"image":[109,221],"priors,":[110],"leading":[111],"degraded":[113],"reconstruction":[114,225,244],"performance.":[115,226],"In":[116],"this":[117],"paper,":[118],"we":[119,179],"propose":[120],"novel":[122],"re-visible":[123,142],"dual-domain":[124,143],"unfolding":[127],"network":[128],"address":[130],"these":[131],"issues":[132],"when":[133],"only":[134],"available.":[138],"Specifically,":[139],"incorporating":[141],"loss,":[144],"all":[145,172],"utilized":[150],"during":[151],"mitigate":[154],"caused":[159],"partitioning.":[162],"This":[163],"design":[164,180],"enables":[165],"model":[167,214],"implicitly":[169],"adapt":[170],"input.":[177],"Deep":[182],"Unfolding":[183],"Network":[184],"based":[185],"Chambolle":[187],"Pock":[189],"Proximal":[190],"Point":[191],"Algorithm":[192],"(DUN-CP-PPA)":[193],"achieve":[195],"end-to-end":[196],"reconstruction.":[197],"By":[198],"employing":[199],"Spatial-Frequency":[201],"Feature":[202],"Extraction":[203],"(SFFE)":[204],"block":[205],"capture":[207],"both":[208,229],"global":[209],"local":[211],"representations,":[212],"integrates":[216],"imaging":[217],"physics":[218],"with":[219],"priors":[222],"enhance":[224],"Experiments":[227],"single-coil":[230],"multi-coil":[232],"that":[235],"our":[236],"method":[237],"outperforms":[238],"state-of-the-art":[239],"approaches":[240],"terms":[242],"of":[243],"performance":[245],"generalization":[247],"capability.":[248]},"counts_by_year":[],"updated_date":"2026-07-07T06:14:10.401900","created_date":"2025-12-23T00:00:00"}