{"id":"https://openalex.org/W4213439152","doi":"https://doi.org/10.1109/tmi.2022.3153849","title":"Pyramid Convolutional RNN for MRI Image Reconstruction","display_name":"Pyramid Convolutional RNN for MRI Image Reconstruction","publication_year":2022,"publication_date":"2022-02-22","ids":{"openalex":"https://openalex.org/W4213439152","doi":"https://doi.org/10.1109/tmi.2022.3153849","pmid":"https://pubmed.ncbi.nlm.nih.gov/35192462"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2022.3153849","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2022.3153849","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/A5014821487","display_name":"Eric Z. Chen","orcid":"https://orcid.org/0000-0001-5002-720X"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Eric Z. Chen","raw_affiliation_strings":["United Imaging Intelligence, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"United Imaging Intelligence, Cambridge, MA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014463024","display_name":"Puyang Wang","orcid":"https://orcid.org/0000-0003-2657-6051"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Puyang Wang","raw_affiliation_strings":["United Imaging Intelligence, Cambridge, MA, USA","Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"United Imaging Intelligence, Cambridge, MA, USA","institution_ids":[]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101998866","display_name":"Xiao Chen","orcid":"https://orcid.org/0000-0002-7147-7311"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao Chen","raw_affiliation_strings":["United Imaging Intelligence, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"United Imaging Intelligence, Cambridge, MA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038526207","display_name":"Terrence Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Terrence Chen","raw_affiliation_strings":["United Imaging Intelligence, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"United Imaging Intelligence, Cambridge, MA, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087112236","display_name":"Shanhui Sun","orcid":"https://orcid.org/0000-0001-9841-8592"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shanhui Sun","raw_affiliation_strings":["United Imaging Intelligence, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"United Imaging Intelligence, Cambridge, MA, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5014821487"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":8.4966,"has_fulltext":false,"cited_by_count":61,"citation_normalized_percentile":{"value":0.98505293,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"41","issue":"8","first_page":"2033","last_page":"2047"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":1.0,"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":1.0,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9998000264167786,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.998199999332428,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7820301055908203},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.725386917591095},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.7120612859725952},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.5907711386680603},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5790210962295532},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5629063844680786},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5014481544494629},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.495837539434433},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45207077264785767},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.43026307225227356},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.12075760960578918},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09873801469802856}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7820301055908203},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.725386917591095},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.7120612859725952},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.5907711386680603},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5790210962295532},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5629063844680786},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5014481544494629},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.495837539434433},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45207077264785767},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.43026307225227356},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.12075760960578918},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09873801469802856},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[{"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":"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":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/tmi.2022.3153849","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2022.3153849","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:35192462","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35192462","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":[{"score":0.49000000953674316,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":154,"referenced_works":["https://openalex.org/W8437397","https://openalex.org/W1901129140","https://openalex.org/W1978333359","https://openalex.org/W2003271614","https://openalex.org/W2029816571","https://openalex.org/W2092663520","https://openalex.org/W2109255472","https://openalex.org/W2111388536","https://openalex.org/W2142808775","https://openalex.org/W2145519820","https://openalex.org/W2167396304","https://openalex.org/W2430196102","https://openalex.org/W2552808051","https://openalex.org/W2560023338","https://openalex.org/W2565639579","https://openalex.org/W2593649546","https://openalex.org/W2604388535","https://openalex.org/W2604451232","https://openalex.org/W2607264901","https://openalex.org/W2611467245","https://openalex.org/W2620324432","https://openalex.org/W2624086852","https://openalex.org/W2731027211","https://openalex.org/W2753160622","https://openalex.org/W2753305843","https://openalex.org/W2773850766","https://openalex.org/W2778924750","https://openalex.org/W2781600508","https://openalex.org/W2785239769","https://openalex.org/W2791621240","https://openalex.org/W2795380527","https://openalex.org/W2798559986","https://openalex.org/W2808361645","https://openalex.org/W2809834193","https://openalex.org/W2883105305","https://openalex.org/W2889995282","https://openalex.org/W2900756484","https://openalex.org/W2914483840","https://openalex.org/W2922528425","https://openalex.org/W2922902233","https://openalex.org/W2944761405","https://openalex.org/W2947859416","https://openalex.org/W2949582403","https://openalex.org/W2950936580","https://openalex.org/W2956625312","https://openalex.org/W2962734274","https://openalex.org/W2963354015","https://openalex.org/W2963682501","https://openalex.org/W2963775850","https://openalex.org/W2964013315","https://openalex.org/W2964153283","https://openalex.org/W2964267765","https://openalex.org/W2964293140","https://openalex.org/W2969785455","https://openalex.org/W2970803305","https://openalex.org/W2970936390","https://openalex.org/W2972061446","https://openalex.org/W2975342646","https://openalex.org/W2979496784","https://openalex.org/W2979588445","https://openalex.org/W2979793468","https://openalex.org/W2985068832","https://openalex.org/W2991684829","https://openalex.org/W2994110075","https://openalex.org/W2995286437","https://openalex.org/W2995582197","https://openalex.org/W2996260215","https://openalex.org/W2996927594","https://openalex.org/W2999167634","https://openalex.org/W2999511788","https://openalex.org/W3000314771","https://openalex.org/W3001319253","https://openalex.org/W3001554227","https://openalex.org/W3004715589","https://openalex.org/W3004778690","https://openalex.org/W3005969576","https://openalex.org/W3012096086","https://openalex.org/W3015993445","https://openalex.org/W3027093788","https://openalex.org/W3027808525","https://openalex.org/W3033822002","https://openalex.org/W3034223847","https://openalex.org/W3034546843","https://openalex.org/W3035300465","https://openalex.org/W3035596626","https://openalex.org/W3035990856","https://openalex.org/W3041188943","https://openalex.org/W3047397044","https://openalex.org/W3047706622","https://openalex.org/W3048743885","https://openalex.org/W3049664569","https://openalex.org/W3083045703","https://openalex.org/W3088638675","https://openalex.org/W3092324452","https://openalex.org/W3092530614","https://openalex.org/W3097194025","https://openalex.org/W3097597433","https://openalex.org/W3100730608","https://openalex.org/W3101326879","https://openalex.org/W3101335681","https://openalex.org/W3102087754","https://openalex.org/W3105403262","https://openalex.org/W3120951298","https://openalex.org/W3137965023","https://openalex.org/W3157723514","https://openalex.org/W3163842339","https://openalex.org/W3163954017","https://openalex.org/W3172058019","https://openalex.org/W3179813600","https://openalex.org/W3186314696","https://openalex.org/W3188455524","https://openalex.org/W3194394433","https://openalex.org/W3216102226","https://openalex.org/W4226133625","https://openalex.org/W4249760698","https://openalex.org/W4286851301","https://openalex.org/W4287179701","https://openalex.org/W4288089920","https://openalex.org/W4288102849","https://openalex.org/W4300001399","https://openalex.org/W4300971732","https://openalex.org/W4301054805","https://openalex.org/W6600324250","https://openalex.org/W6714477741","https://openalex.org/W6717367658","https://openalex.org/W6717870063","https://openalex.org/W6729433768","https://openalex.org/W6734652334","https://openalex.org/W6735961515","https://openalex.org/W6738960811","https://openalex.org/W6739653404","https://openalex.org/W6743661861","https://openalex.org/W6745921498","https://openalex.org/W6748645028","https://openalex.org/W6755308174","https://openalex.org/W6755625687","https://openalex.org/W6766196973","https://openalex.org/W6767150047","https://openalex.org/W6767156836","https://openalex.org/W6767273182","https://openalex.org/W6767820389","https://openalex.org/W6768631097","https://openalex.org/W6769530646","https://openalex.org/W6771651061","https://openalex.org/W6773549387","https://openalex.org/W6779595999","https://openalex.org/W6780455530","https://openalex.org/W6781581958","https://openalex.org/W6782734980","https://openalex.org/W6792219651","https://openalex.org/W6794570189","https://openalex.org/W6795040098","https://openalex.org/W6804408792","https://openalex.org/W6948377561"],"related_works":["https://openalex.org/W4225394202","https://openalex.org/W4298287631","https://openalex.org/W2953061907","https://openalex.org/W3032952384","https://openalex.org/W3034302643","https://openalex.org/W1847088711","https://openalex.org/W3036642985","https://openalex.org/W1928301487","https://openalex.org/W2151220638","https://openalex.org/W2725829804"],"abstract_inverted_index":{"Fast":[0],"and":[1,95,137,172,175,186],"accurate":[2],"MRI":[3,62],"image":[4,117],"reconstruction":[5,17,63,122],"from":[6,30,54],"undersampled":[7,31],"data":[8,32,136,154],"is":[9,33,150,194],"crucial":[10],"in":[11,23,84,106,200],"clinical":[12],"practice.":[13],"Deep":[14],"learning":[15,44],"based":[16,45],"methods":[18,123,185],"have":[19],"shown":[20],"promising":[21],"advances":[22],"recent":[24],"years.":[25],"However,":[26],"recovering":[27],"fine":[28],"details":[29],"still":[34],"challenging.":[35],"In":[36],"this":[37],"paper,":[38],"we":[39,68],"introduce":[40],"a":[41,102,107,115],"novel":[42],"deep":[43],"method,":[46],"Pyramid":[47],"Convolutional":[48],"RNN":[49,76],"(PC-RNN),":[50],"to":[51,79,152,160],"reconstruct":[52],"images":[53,91,98],"multiple":[55,85,141],"scales.":[56,86],"Based":[57],"on":[58,168],"the":[59,70,82,96,140,169,176,180,197,201],"formulation":[60],"of":[61,196],"as":[64,143],"an":[65],"inverse":[66],"problem,":[67],"design":[69],"PC-RNN":[71,127],"model":[72,139,167,182],"with":[73,155],"three":[74],"convolutional":[75],"(ConvRNN)":[77],"modules":[78,113],"iteratively":[80],"learn":[81,114],"features":[83],"Each":[87],"ConvRNN":[88,112],"module":[89,105],"reconstructs":[90],"at":[92],"different":[93],"scales":[94],"reconstructed":[97],"are":[99],"combined":[100],"by":[101],"final":[103],"CNN":[104],"pyramid":[108],"fashion.":[109],"The":[110,146,191],"multi-scale":[111],"coarse-to-fine":[116],"reconstruction.":[118],"Unlike":[119],"other":[120,184],"common":[121],"for":[124,134],"parallel":[125],"imaging,":[126],"does":[128],"not":[129],"employ":[130],"coil":[131,147,157],"sensitive":[132],"maps":[133],"multi-coil":[135],"directly":[138],"coils":[142],"multi-channel":[144],"inputs.":[145],"compression":[148],"technique":[149],"applied":[151],"standardize":[153],"various":[156],"numbers,":[158],"leading":[159],"more":[161,189],"efficient":[162],"training.":[163],"We":[164],"evaluate":[165],"our":[166],"fastMRI":[170,203],"knee":[171],"brain":[173],"datasets":[174],"results":[177],"show":[178],"that":[179],"proposed":[181,192],"outperforms":[183],"can":[187],"recover":[188],"details.":[190],"method":[193],"one":[195],"winner":[198],"solutions":[199],"2019":[202],"competition.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":18},{"year":2024,"cited_by_count":26},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}