{"id":"https://openalex.org/W2142808775","doi":"https://doi.org/10.1109/tmi.2010.2093536","title":"Parallel MR Image Reconstruction Using Augmented Lagrangian Methods","display_name":"Parallel MR Image Reconstruction Using Augmented Lagrangian Methods","publication_year":2010,"publication_date":"2010-11-23","ids":{"openalex":"https://openalex.org/W2142808775","doi":"https://doi.org/10.1109/tmi.2010.2093536","mag":"2142808775","pmid":"https://pubmed.ncbi.nlm.nih.gov/21095861"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2010.2093536","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2010.2093536","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":true,"oa_status":"green","oa_url":"https://hdl.handle.net/2027.42/85846","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108524187","display_name":"S. Ramani","orcid":null},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"S Ramani","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA. sramani@umich.edu","Dept. of Electr. Eng. & Comput. Sci., Univ. of Michigan, Ann Arbor, MI, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA. sramani@umich.edu","institution_ids":["https://openalex.org/I27837315"]},{"raw_affiliation_string":"Dept. of Electr. Eng. & Comput. Sci., Univ. of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027207271","display_name":"Jeffrey A. Fessler","orcid":"https://orcid.org/0000-0001-9998-3315"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J A Fessler","raw_affiliation_strings":["University of Michigan, Ann Arbor, MI, US","Dept. of Electr. Eng. & Comput. Sci., Univ. of Michigan, Ann Arbor, MI, USA"],"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, MI, US","institution_ids":["https://openalex.org/I27837315"]},{"raw_affiliation_string":"Dept. of Electr. Eng. & Comput. Sci., Univ. of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5108524187"],"corresponding_institution_ids":["https://openalex.org/I27837315"],"apc_list":null,"apc_paid":null,"fwci":13.7282,"has_fulltext":true,"cited_by_count":229,"citation_normalized_percentile":{"value":0.99318748,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"30","issue":"3","first_page":"694","last_page":"706"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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/T10378","display_name":"Advanced MRI 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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9997000098228455,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/augmented-lagrangian-method","display_name":"Augmented Lagrangian method","score":0.8946447372436523},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5892711877822876},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.5763878226280212},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5374513268470764},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5180709362030029},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5093599557876587},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.5017285346984863},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4721401035785675},{"id":"https://openalex.org/keywords/conjugate-gradient-method","display_name":"Conjugate gradient method","score":0.44128337502479553},{"id":"https://openalex.org/keywords/aliasing","display_name":"Aliasing","score":0.43000102043151855},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.4271089732646942},{"id":"https://openalex.org/keywords/nonlinear-conjugate-gradient-method","display_name":"Nonlinear conjugate gradient method","score":0.42083364725112915},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3916494846343994},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2833317220211029},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.20074978470802307},{"id":"https://openalex.org/keywords/undersampling","display_name":"Undersampling","score":0.15463310480117798},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.13061296939849854}],"concepts":[{"id":"https://openalex.org/C150452318","wikidata":"https://www.wikidata.org/wiki/Q4820432","display_name":"Augmented Lagrangian method","level":2,"score":0.8946447372436523},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5892711877822876},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5763878226280212},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5374513268470764},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5180709362030029},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5093599557876587},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.5017285346984863},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4721401035785675},{"id":"https://openalex.org/C81184566","wikidata":"https://www.wikidata.org/wiki/Q1191895","display_name":"Conjugate gradient method","level":2,"score":0.44128337502479553},{"id":"https://openalex.org/C4069607","wikidata":"https://www.wikidata.org/wiki/Q868732","display_name":"Aliasing","level":3,"score":0.43000102043151855},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.4271089732646942},{"id":"https://openalex.org/C26362088","wikidata":"https://www.wikidata.org/wiki/Q17086453","display_name":"Nonlinear conjugate gradient method","level":4,"score":0.42083364725112915},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3916494846343994},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2833317220211029},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.20074978470802307},{"id":"https://openalex.org/C136536468","wikidata":"https://www.wikidata.org/wiki/Q1225894","display_name":"Undersampling","level":2,"score":0.15463310480117798},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.13061296939849854},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","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":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","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":true},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001921","descriptor_name":"Brain","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":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007089","descriptor_name":"Image Enhancement","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007089","descriptor_name":"Image Enhancement","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007089","descriptor_name":"Image Enhancement","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007089","descriptor_name":"Image Enhancement","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016477","descriptor_name":"Artifacts","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016477","descriptor_name":"Artifacts","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016477","descriptor_name":"Artifacts","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016477","descriptor_name":"Artifacts","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":4,"locations":[{"id":"doi:10.1109/tmi.2010.2093536","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2010.2093536","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:21095861","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/21095861","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},{"id":"pmh:oai:deepblue.lib.umich.edu:2027.42/85846","is_oa":true,"landing_page_url":"http://hdl.handle.net/2027.42/85846>","pdf_url":"https://hdl.handle.net/2027.42/85846","source":{"id":"https://openalex.org/S4306400393","display_name":"Deep Blue (University of Michigan)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I27837315","host_organization_name":"University of Michigan","host_organization_lineage":["https://openalex.org/I27837315"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:3081617","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/3081617","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Trans Med Imaging","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:deepblue.lib.umich.edu:2027.42/85846","is_oa":true,"landing_page_url":"http://hdl.handle.net/2027.42/85846>","pdf_url":"https://hdl.handle.net/2027.42/85846","source":{"id":"https://openalex.org/S4306400393","display_name":"Deep Blue (University of Michigan)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I27837315","host_organization_name":"University of Michigan","host_organization_lineage":["https://openalex.org/I27837315"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4621158401","display_name":null,"funder_award_id":"Fellowship","funder_id":"https://openalex.org/F4320320924","funder_display_name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung"},{"id":"https://openalex.org/G6894402473","display_name":null,"funder_award_id":"Fellowship","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8273602072","display_name":null,"funder_award_id":"P01 CA87634","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8521217850","display_name":"Data-driven optimization of algorithm parameters for regularized image reconstruction","funder_award_id":"125446","funder_id":"https://openalex.org/F4320320924","funder_display_name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung"},{"id":"https://openalex.org/G8742234846","display_name":"Die temporale Struktur von ostschweizerdeutschen Lauten. Eine instrumentalphonetische Untersuchung.","funder_award_id":"25446","funder_id":"https://openalex.org/F4320320924","funder_display_name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320320924","display_name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung","ror":"https://ror.org/00yjd3n13"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2142808775.pdf","grobid_xml":"https://content.openalex.org/works/W2142808775.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W118540534","https://openalex.org/W368078881","https://openalex.org/W955428205","https://openalex.org/W1965519200","https://openalex.org/W1971571088","https://openalex.org/W1978333359","https://openalex.org/W1983579205","https://openalex.org/W1996287810","https://openalex.org/W1999584433","https://openalex.org/W2005041367","https://openalex.org/W2045079045","https://openalex.org/W2072286452","https://openalex.org/W2077237786","https://openalex.org/W2089508486","https://openalex.org/W2100556411","https://openalex.org/W2100705753","https://openalex.org/W2101675075","https://openalex.org/W2102462706","https://openalex.org/W2104861988","https://openalex.org/W2105266774","https://openalex.org/W2117700900","https://openalex.org/W2123031198","https://openalex.org/W2138075502","https://openalex.org/W2140818347","https://openalex.org/W2142058898","https://openalex.org/W2142224912","https://openalex.org/W2145020729","https://openalex.org/W2148791483","https://openalex.org/W2151354228","https://openalex.org/W2156457848","https://openalex.org/W2158252006","https://openalex.org/W2167233877","https://openalex.org/W2167396304","https://openalex.org/W2168543121","https://openalex.org/W2169049514","https://openalex.org/W3029645440","https://openalex.org/W3106359998","https://openalex.org/W3121742466","https://openalex.org/W4249760698","https://openalex.org/W4250438881","https://openalex.org/W4293775970","https://openalex.org/W6684531467"],"related_works":["https://openalex.org/W2098528027","https://openalex.org/W2375129592","https://openalex.org/W2060532089","https://openalex.org/W3159557833","https://openalex.org/W2005717169","https://openalex.org/W2183734858","https://openalex.org/W4387168483","https://openalex.org/W4319027779","https://openalex.org/W2941778027","https://openalex.org/W3131790919"],"abstract_inverted_index":{"Magnetic":[0],"resonance":[1],"image":[2,24],"(MRI)":[3],"reconstruction":[4,42],"using":[5,80,93],"SENSitivity":[6],"Encoding":[7],"(SENSE)":[8],"requires":[9],"regularization":[10,20],"to":[11,73,99,111],"suppress":[12],"noise":[13],"and":[14,18,69,123,131,138,162],"aliasing":[15],"effects.":[16],"Edge-preserving":[17],"sparsity-based":[19],"criteria":[21,130],"can":[22,102],"improve":[23],"quality,":[25],"but":[26],"they":[27],"demand":[28],"computation-intensive":[29],"nonlinear":[30,158],"optimization.":[31],"In":[32],"this":[33],"paper,":[34],"we":[35],"present":[36],"novel":[37],"methods":[38,108],"for":[39,53],"regularized":[40,62],"MRI":[41],"from":[43],"undersampled":[44],"sensitivity":[45],"encoded":[46],"data--SENSE-reconstruction--using":[47],"the":[48,145],"augmented":[49],"Lagrangian":[50],"(AL)":[51],"framework":[52,92],"solving":[54],"large-scale":[55],"constrained":[56,78,87],"optimization":[57,67,154],"problems.":[58],"We":[59,83],"first":[60],"formulate":[61],"SENSE-reconstruction":[63],"as":[64,157],"an":[65,90,94],"unconstrained":[66],"task":[68],"then":[70,84],"convert":[71],"it":[72],"a":[74,112],"set":[75],"of":[76,115,127],"(equivalent)":[77],"problems":[79],"variable":[81],"splitting.":[82],"attack":[85],"these":[86],"versions":[88],"in":[89,139],"AL":[91,147],"alternating":[95],"minimization":[96],"method,":[97],"leading":[98],"algorithms":[100,148,155],"that":[101,117,144],"be":[103],"implemented":[104],"easily.":[105],"The":[106],"proposed":[107,146],"are":[109],"applicable":[110],"general":[113],"class":[114],"regularizers":[116],"includes":[118],"popular":[119],"edge-preserving":[120],"(e.g.,":[121,125],"total-variation)":[122],"sparsity-promoting":[124],"l(1)-norm":[126],"wavelet":[128],"coefficients)":[129],"combinations":[132],"thereof.":[133],"Numerical":[134],"experiments":[135],"with":[136],"synthetic":[137],"vivo":[140],"human":[141],"data":[142],"illustrate":[143],"converge":[149],"faster":[150],"than":[151],"both":[152],"general-purpose":[153],"such":[156],"conjugate":[159],"gradient":[160],"(NCG)":[161],"state-of-the-art":[163],"MFISTA.":[164]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":22},{"year":2018,"cited_by_count":18},{"year":2017,"cited_by_count":16},{"year":2016,"cited_by_count":26},{"year":2015,"cited_by_count":22},{"year":2014,"cited_by_count":19},{"year":2013,"cited_by_count":24},{"year":2012,"cited_by_count":14}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
