{"id":"https://openalex.org/W1966339986","doi":"https://doi.org/10.1117/12.2064260","title":"Nuclear norm-regularized k-space-based parallel imaging reconstruction","display_name":"Nuclear norm-regularized k-space-based parallel imaging reconstruction","publication_year":2014,"publication_date":"2014-04-16","ids":{"openalex":"https://openalex.org/W1966339986","doi":"https://doi.org/10.1117/12.2064260","mag":"1966339986"},"language":"en","primary_location":{"id":"doi:10.1117/12.2064260","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2064260","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5101648296","display_name":"Lin Xu","orcid":"https://orcid.org/0009-0005-6484-7811"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Xu","raw_affiliation_strings":["Univ. of Electronic Science and Technology of China (China)","Univ. of Electronic Science and Technology of China  (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of Electronic Science and Technology of China (China)","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"Univ. of Electronic Science and Technology of China  (China)","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100776315","display_name":"Xiaoyun Liu","orcid":"https://orcid.org/0000-0002-9838-1109"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyun Liu","raw_affiliation_strings":["Univ. of Electronic Science and Technology of China (China)","Univ. of Electronic Science and Technology of China  (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of Electronic Science and Technology of China (China)","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"Univ. of Electronic Science and Technology of China  (China)","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05016827,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"9159","issue":null,"first_page":"91590Z","last_page":"91590Z"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/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/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9991999864578247,"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/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.6997174620628357},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6560288667678833},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6019781827926636},{"id":"https://openalex.org/keywords/k-space","display_name":"k-space","score":0.5495749711990356},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5487353801727295},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.5348955988883972},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.5202387571334839},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.43506595492362976},{"id":"https://openalex.org/keywords/matrix-norm","display_name":"Matrix norm","score":0.4323709309101105},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.4285601079463959},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.4185764491558075},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3795052766799927},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34584516286849976},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3380895256996155},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.32789063453674316},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22331354022026062},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.08720219135284424}],"concepts":[{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.6997174620628357},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6560288667678833},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6019781827926636},{"id":"https://openalex.org/C197413143","wikidata":"https://www.wikidata.org/wiki/Q1050490","display_name":"k-space","level":3,"score":0.5495749711990356},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5487353801727295},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.5348955988883972},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.5202387571334839},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.43506595492362976},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.4323709309101105},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.4285601079463959},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.4185764491558075},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3795052766799927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34584516286849976},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3380895256996155},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.32789063453674316},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22331354022026062},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.08720219135284424},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","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},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2064260","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2064260","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5,"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":9,"referenced_works":["https://openalex.org/W19536506","https://openalex.org/W212537071","https://openalex.org/W2045079045","https://openalex.org/W2047071281","https://openalex.org/W2049299851","https://openalex.org/W2145096794","https://openalex.org/W4238237960","https://openalex.org/W4250955649","https://openalex.org/W6662220948"],"related_works":["https://openalex.org/W2896778670","https://openalex.org/W2187562763","https://openalex.org/W2907262162","https://openalex.org/W2212041357","https://openalex.org/W2339684922","https://openalex.org/W36742526","https://openalex.org/W2895530314","https://openalex.org/W2087332491","https://openalex.org/W3191591176","https://openalex.org/W2434806794"],"abstract_inverted_index":{"Parallel":[0],"imaging":[1,42,58,120],"reconstruction":[2,59,66],"suffers":[3],"from":[4],"serious":[5],"noise":[6,133],"amplification":[7],"at":[8,134],"high":[9,135],"accelerations":[10,136],"that":[11,125],"can":[12],"be":[13],"alleviated":[14],"with":[15],"regularization":[16],"by":[17,114],"imposing":[18],"some":[19],"prior":[20,37,81],"information":[21,38,82],"or":[22,85],"constraints":[23],"on":[24,83],"image.":[25],"Nevertheless,":[26],"point-wise":[27],"interpolation":[28],"of":[29,36,67,79,96,100,131],"missing":[30,68],"k-space":[31,55],"data":[32,69],"restricts":[33],"the":[34,65,89,93,115,126],"use":[35],"in":[39,137],"k-space-based":[40],"parallel":[41,57],"reconstructions":[43],"like":[44],"generalized":[45],"auto-calibrating":[46],"partial":[47],"acquisitions":[48],"(GRAPPA).":[49],"In":[50],"this":[51],"study,":[52],"a":[53,71,74,109],"regularized":[54],"based":[56],"is":[60,129],"presented.":[61],"We":[62],"first":[63],"formulate":[64],"within":[70],"patch":[72],"as":[73],"linear":[75],"inverse":[76],"problem.":[77],"Instead":[78],"exploiting":[80],"image":[84],"its":[86],"transform":[87],"domain,":[88],"proposed":[90,127],"method":[91,128],"exploits":[92],"rank":[94],"deficiency":[95],"structured":[97],"matrix":[98],"consisting":[99],"vectorized":[101],"patches":[102],"form":[103],"entire":[104],"k-space,":[105],"which":[106],"leads":[107],"to":[108],"nuclear":[110],"norm-regularized":[111],"problem":[112],"solved":[113],"numeric":[116],"algorithms":[117],"iteratively.":[118],"Brain":[119],"studies":[121],"are":[122],"performed,":[123],"demonstrating":[124],"capable":[130],"mitigating":[132],"GRAPPA":[138],"reconstruction.":[139]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
