{"id":"https://openalex.org/W2949402056","doi":"https://doi.org/10.1109/tmi.2019.2932961","title":"Coupled Dictionary Learning for Multi-Contrast MRI Reconstruction","display_name":"Coupled Dictionary Learning for Multi-Contrast MRI Reconstruction","publication_year":2019,"publication_date":"2019-08-02","ids":{"openalex":"https://openalex.org/W2949402056","doi":"https://doi.org/10.1109/tmi.2019.2932961","mag":"2949402056","pmid":"https://pubmed.ncbi.nlm.nih.gov/31395541"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2019.2932961","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2019.2932961","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":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1806.09930","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Pingfan Song","orcid":"https://orcid.org/0000-0003-3596-083X"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]},{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Pingfan Song","raw_affiliation_strings":["Department of Electronic and Electrical Engineering, Imperial College London, London, U.K","Department of Electronic and Electrical Engineering, University College London, London, U.K"],"raw_orcid":"https://orcid.org/0000-0003-3596-083X","affiliations":[{"raw_affiliation_string":"Department of Electronic and Electrical Engineering, Imperial College London, London, U.K","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"Department of Electronic and Electrical Engineering, University College London, London, U.K","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lior Weizman","orcid":null},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Lior Weizman","raw_affiliation_strings":["Department of Electrical Engineering, Technion \u2013 Israel Institute of Technology, Haifa, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Technion \u2013 Israel Institute of Technology, Haifa, Israel","institution_ids":["https://openalex.org/I174306211"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Joao F. C. Mota","orcid":"https://orcid.org/0000-0001-7263-8255"},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]},{"id":"https://openalex.org/I4210085930","display_name":"Heriot-Watt University Malaysia","ror":"https://ror.org/0059w0420","country_code":"MY","type":"education","lineage":["https://openalex.org/I4210085930"]}],"countries":["GB","MY"],"is_corresponding":false,"raw_author_name":"Joao F. C. Mota","raw_affiliation_strings":["Department of School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, U.K"],"raw_orcid":"https://orcid.org/0000-0001-7263-8255","affiliations":[{"raw_affiliation_string":"Department of School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, U.K","institution_ids":["https://openalex.org/I32062511","https://openalex.org/I4210085930"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yonina C. Eldar","orcid":"https://orcid.org/0000-0003-4358-5304"},"institutions":[{"id":"https://openalex.org/I53964585","display_name":"Weizmann Institute of Science","ror":"https://ror.org/0316ej306","country_code":"IL","type":"education","lineage":["https://openalex.org/I53964585"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Yonina C. Eldar","raw_affiliation_strings":["Faculty of Mathematics and Computer Science, Weizmann Institute of Science, Rehovot, Israel"],"raw_orcid":"https://orcid.org/0000-0003-4358-5304","affiliations":[{"raw_affiliation_string":"Faculty of Mathematics and Computer Science, Weizmann Institute of Science, Rehovot, Israel","institution_ids":["https://openalex.org/I53964585"]}]},{"author_position":"last","author":{"id":null,"display_name":"Miguel R. D. Rodrigues","orcid":"https://orcid.org/0000-0002-8908-847X"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Miguel R. D. Rodrigues","raw_affiliation_strings":["Department of Electronic and Electrical Engineering, University College London, London, U.K"],"raw_orcid":"https://orcid.org/0000-0002-8908-847X","affiliations":[{"raw_affiliation_string":"Department of Electronic and Electrical Engineering, University College London, London, U.K","institution_ids":["https://openalex.org/I45129253"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.0448,"has_fulltext":false,"cited_by_count":74,"citation_normalized_percentile":{"value":0.9682259,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"39","issue":"3","first_page":"621","last_page":"633"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.3767000138759613,"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":0.3767000138759613,"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":0.29319998621940613,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.06340000033378601,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/dictionary-learning","display_name":"Dictionary learning","score":0.6168000102043152},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.6014999747276306},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.5940999984741211},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5882999897003174},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.42669999599456787},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.4034000039100647},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.37700000405311584},{"id":"https://openalex.org/keywords/aliasing","display_name":"Aliasing","score":0.3711000084877014},{"id":"https://openalex.org/keywords/k-svd","display_name":"K-SVD","score":0.3474999964237213},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.3465000092983246}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7260000109672546},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7087000012397766},{"id":"https://openalex.org/C2988886741","wikidata":"https://www.wikidata.org/wiki/Q25304494","display_name":"Dictionary learning","level":3,"score":0.6168000102043152},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.6014999747276306},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5940999984741211},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5882999897003174},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.42669999599456787},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.4034000039100647},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39590001106262207},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.37700000405311584},{"id":"https://openalex.org/C4069607","wikidata":"https://www.wikidata.org/wiki/Q868732","display_name":"Aliasing","level":3,"score":0.3711000084877014},{"id":"https://openalex.org/C154771677","wikidata":"https://www.wikidata.org/wiki/Q17098361","display_name":"K-SVD","level":3,"score":0.3474999964237213},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.3465000092983246},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.3458000123500824},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.3287000060081482},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.32510000467300415},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.31299999356269836},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.3052000105381012},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3046000003814697},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.3034999966621399},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.2978000044822693},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.2752000093460083},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C157787499","wikidata":"https://www.wikidata.org/wiki/Q13479657","display_name":"Real-time MRI","level":3,"score":0.2720000147819519},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.26820001006126404},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.2669000029563904},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.2655999958515167},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2612999975681305},{"id":"https://openalex.org/C140479938","wikidata":"https://www.wikidata.org/wiki/Q5254619","display_name":"Iterated function","level":2,"score":0.25949999690055847},{"id":"https://openalex.org/C131720326","wikidata":"https://www.wikidata.org/wiki/Q5196075","display_name":"Curvelet","level":4,"score":0.2563000023365021},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.25450000166893005}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","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":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":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003287","descriptor_name":"Contrast Media","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003287","descriptor_name":"Contrast Media","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003287","descriptor_name":"Contrast Media","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":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1109/tmi.2019.2932961","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2019.2932961","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:31395541","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31395541","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:arXiv.org:1806.09930","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1806.09930","pdf_url":"https://arxiv.org/pdf/1806.09930","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:spiral.imperial.ac.uk:10044/1/75627","is_oa":false,"landing_page_url":"http://hdl.handle.net/10044/1/75627","pdf_url":null,"source":{"id":"https://openalex.org/S4306401396","display_name":"Spiral (Imperial College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I47508984","host_organization_name":"Imperial College London","host_organization_lineage":["https://openalex.org/I47508984"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"633","raw_type":"Journal Article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1806.09930","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1806.09930","pdf_url":"https://arxiv.org/pdf/1806.09930","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3163032127","display_name":"Efficient Energy Management in Energy Harvesting Wireless Sensor Networks: An Approach Based on Distributed Compressive Sensing","funder_award_id":"EP/K033166/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G3695359952","display_name":null,"funder_award_id":"IE160348","funder_id":"https://openalex.org/F4320320006","funder_display_name":"Royal Society"},{"id":"https://openalex.org/G6084913331","display_name":null,"funder_award_id":"EP/K033166/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G738928039","display_name":null,"funder_award_id":"335/14","funder_id":"https://openalex.org/F4320322252","funder_display_name":"Israel Science Foundation"},{"id":"https://openalex.org/G7842005466","display_name":null,"funder_award_id":"Horizon 2020","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320006","display_name":"Royal Society","ror":"https://ror.org/03wnrjx87"},{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320322252","display_name":"Israel Science Foundation","ror":"https://ror.org/04sazxf24"},{"id":"https://openalex.org/F4320323706","display_name":"Ministry of Science and Technology, Israel","ror":"https://ror.org/02heb2n75"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W1510815927","https://openalex.org/W1918311561","https://openalex.org/W1972898607","https://openalex.org/W1973875179","https://openalex.org/W2035808554","https://openalex.org/W2043981719","https://openalex.org/W2067812381","https://openalex.org/W2093621384","https://openalex.org/W2099944953","https://openalex.org/W2101675075","https://openalex.org/W2117882039","https://openalex.org/W2119047398","https://openalex.org/W2127271355","https://openalex.org/W2131658309","https://openalex.org/W2134884567","https://openalex.org/W2136390628","https://openalex.org/W2141168890","https://openalex.org/W2143794369","https://openalex.org/W2144288697","https://openalex.org/W2145096794","https://openalex.org/W2146420155","https://openalex.org/W2152732392","https://openalex.org/W2160547390","https://openalex.org/W2163973643","https://openalex.org/W2167577940","https://openalex.org/W2168668658","https://openalex.org/W2175306913","https://openalex.org/W2281493160","https://openalex.org/W2413432410","https://openalex.org/W2494581537","https://openalex.org/W2536674126","https://openalex.org/W2552808051","https://openalex.org/W2556214332","https://openalex.org/W2560815146","https://openalex.org/W2745398223","https://openalex.org/W2778924750","https://openalex.org/W2797196654","https://openalex.org/W2806754378","https://openalex.org/W2810581099","https://openalex.org/W2918763530","https://openalex.org/W2950936580","https://openalex.org/W2963334250","https://openalex.org/W2963793388","https://openalex.org/W4206310440","https://openalex.org/W4241161896","https://openalex.org/W4250955649","https://openalex.org/W4300263211","https://openalex.org/W6676727762","https://openalex.org/W6684531467","https://openalex.org/W6748330889","https://openalex.org/W6785845765","https://openalex.org/W6786032295"],"related_works":[],"abstract_inverted_index":{"Magnetic":[0],"resonance":[1],"(MR)":[2],"imaging":[3,196,203],"tasks":[4],"often":[5],"involve":[6],"multiple":[7,112],"contrasts,":[8,106],"such":[9,204],"as":[10,205],"T1-weighted,":[11],"T2-weighted":[12],"and":[13,29,86,136,151,197],"fluid-attenuated":[14],"inversion":[15],"recovery":[16],"(FLAIR)":[17],"data.":[18,73],"These":[19],"contrasts":[20,62,113,150,168],"capture":[21,109],"information":[22],"associated":[23],"with":[24,169],"the":[25,57,105,122,125,134,139,148,152,155],"same":[26],"underlying":[27],"anatomy":[28],"thus":[30],"exhibit":[31],"similarities":[32],"in":[33,114,138,154,193,200],"either":[34],"structure":[35],"level":[36],"or":[37,65],"gray":[38],"level.":[39],"In":[40],"this":[41],"paper,":[42],"we":[43],"propose":[44],"a":[45,95,115,170],"coupled":[46,80,83,129],"dictionary":[47,81],"learning":[48],"based":[49],"multi-contrast":[50,194],"MRI":[51,167],"reconstruction":[52,67],"(CDLMRI)":[53],"approach":[54,75],"to":[55,104,132],"leverage":[56],"dependency":[58],"correlation":[59],"between":[60,77,147,184],"different":[61,185],"for":[63],"guided":[64],"joint":[66],"from":[68],"their":[69],"under-sampled":[70],"k":[71,88,156],"-space":[72,89,157],"Our":[74],"iterates":[76],"three":[78],"stages:":[79],"learning,":[82],"sparse":[84,116,130],"denoising,":[85],"enforcing":[87],"consistency.":[90],"The":[91,142,187],"first":[92],"stage":[93,127,144],"learns":[94],"set":[96],"of":[97,162,165,172,180],"dictionaries":[98],"that":[99,176],"not":[100],"only":[101],"are":[102],"adaptive":[103],"but":[107],"also":[108],"correlations":[110],"among":[111],"transform":[117],"domain.":[118,158],"By":[119],"capitalizing":[120],"on":[121],"learned":[123,188],"dictionaries,":[124],"second":[126],"performs":[128],"coding":[131],"remove":[133],"aliasing":[135],"noise":[137],"corrupted":[140],"contrasts.":[141,186],"third":[143],"enforces":[145],"consistency":[146],"denoised":[149],"measurements":[153],"Numerical":[159],"experiments,":[160],"consisting":[161],"retrospective":[163],"under-sampling":[164],"various":[166],"variety":[171],"sampling":[173],"schemes,":[174],"demonstrate":[175],"CDLMRI":[177],"is":[178],"capable":[179],"capturing":[181],"structural":[182],"dependencies":[183],"priors":[189],"indicate":[190],"notable":[191],"advantages":[192],"MR":[195,202,206],"promising":[198],"applications":[199],"quantitative":[201],"fingerprinting.":[207]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":8},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-08T08:33:18.762332","created_date":"2019-06-27T00:00:00"}