{"id":"https://openalex.org/W1601616725","doi":"https://doi.org/10.1109/isbi.2015.7164101","title":"Accelerate single-shot data acquisitions using compressed sensing and FRONSAC imaging","display_name":"Accelerate single-shot data acquisitions using compressed sensing and FRONSAC imaging","publication_year":2015,"publication_date":"2015-04-01","ids":{"openalex":"https://openalex.org/W1601616725","doi":"https://doi.org/10.1109/isbi.2015.7164101","mag":"1601616725"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2015.7164101","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2015.7164101","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1502.07226","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015746241","display_name":"Haifeng Wang","orcid":"https://orcid.org/0000-0003-4229-3668"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Haifeng Wang","raw_affiliation_strings":["Department of Diagnostic Radiology, Yale University, New Haven, CT, USA"],"affiliations":[{"raw_affiliation_string":"Department of Diagnostic Radiology, Yale University, New Haven, CT, USA","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079635112","display_name":"R. Todd Constable","orcid":"https://orcid.org/0000-0001-5661-9521"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"R. Todd Constable","raw_affiliation_strings":["Department of Diagnostic Radiology, Yale University, New Haven, CT, USA"],"affiliations":[{"raw_affiliation_string":"Department of Diagnostic Radiology, Yale University, New Haven, CT, USA","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039007799","display_name":"Gigi Galiana","orcid":"https://orcid.org/0000-0001-5974-8708"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gigi Galiana","raw_affiliation_strings":["Department of Diagnostic Radiology, Yale University, New Haven, CT, USA"],"affiliations":[{"raw_affiliation_string":"Department of Diagnostic Radiology, Yale University, New Haven, CT, USA","institution_ids":["https://openalex.org/I32971472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5015746241"],"corresponding_institution_ids":["https://openalex.org/I32971472"],"apc_list":null,"apc_paid":null,"fwci":0.5411,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.6888002,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1252","last_page":"1255"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9998999834060669,"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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/undersampling","display_name":"Undersampling","score":0.9371404647827148},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.8804804086685181},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.665939450263977},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6382853984832764},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.6185770630836487},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.6095314025878906},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.557531476020813},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4768008887767792},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.434704065322876},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39941102266311646},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.151490718126297}],"concepts":[{"id":"https://openalex.org/C136536468","wikidata":"https://www.wikidata.org/wiki/Q1225894","display_name":"Undersampling","level":2,"score":0.9371404647827148},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.8804804086685181},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.665939450263977},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6382853984832764},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.6185770630836487},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.6095314025878906},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.557531476020813},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4768008887767792},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.434704065322876},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39941102266311646},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.151490718126297},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/isbi.2015.7164101","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2015.7164101","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1502.07226","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1502.07226","pdf_url":"https://arxiv.org/pdf/1502.07226","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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1502.07226","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1502.07226","pdf_url":"https://arxiv.org/pdf/1502.07226","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":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1544731538","https://openalex.org/W1898708163","https://openalex.org/W1969758440","https://openalex.org/W1983895383","https://openalex.org/W1986194522","https://openalex.org/W1989991896","https://openalex.org/W1992667716","https://openalex.org/W2021942040","https://openalex.org/W2025286387","https://openalex.org/W2026177799","https://openalex.org/W2047544187","https://openalex.org/W2088896265","https://openalex.org/W2092224074","https://openalex.org/W2101675075","https://openalex.org/W2107906890","https://openalex.org/W2109946292","https://openalex.org/W2111388536","https://openalex.org/W2115660589","https://openalex.org/W2117237746","https://openalex.org/W2117700900","https://openalex.org/W2133758130","https://openalex.org/W2143470728","https://openalex.org/W2145096794","https://openalex.org/W2163956387","https://openalex.org/W2167233877","https://openalex.org/W2167836216","https://openalex.org/W2168319017","https://openalex.org/W2186386031","https://openalex.org/W2188688029","https://openalex.org/W2296616510","https://openalex.org/W2912602012","https://openalex.org/W4249760698","https://openalex.org/W4250955649","https://openalex.org/W4285719527","https://openalex.org/W6632534604","https://openalex.org/W6646698408","https://openalex.org/W6677276500","https://openalex.org/W6680110068","https://openalex.org/W6685335849","https://openalex.org/W6687071887","https://openalex.org/W6758706229"],"related_works":["https://openalex.org/W3011226087","https://openalex.org/W2212041357","https://openalex.org/W2895530314","https://openalex.org/W3214931932","https://openalex.org/W1959447026","https://openalex.org/W2052082011","https://openalex.org/W2903019797","https://openalex.org/W2218273114","https://openalex.org/W2061033783","https://openalex.org/W1994141795"],"abstract_inverted_index":{"Nonlinear":[0,51],"spatial":[1],"encoding":[2,13,71,96],"magnetic":[3],"(SEM)":[4],"fields":[5,59],"have":[6,44],"been":[7],"studied":[8],"to":[9,35,65,103,115],"complement":[10],"multichannel":[11],"RF":[12],"and":[14,26,100,131,149],"accelerate":[15],"MRI":[16],"scans.":[17],"Published":[18],"schemes":[19],"include":[20],"PatLoc,":[21],"O-Space,":[22],"Null":[23],"Space,":[24],"4D-RIO,":[25],"others,":[27],"but":[28],"the":[29,57,77,89,104,127],"large":[30],"variety":[31],"of":[32,129,146],"possible":[33],"approaches":[34],"exploiting":[36],"nonlinear":[37,58],"SEMs":[38],"remains":[39],"mostly":[40],"unexplored.":[41],"Before,":[42],"we":[43],"presented":[45,124],"a":[46,61,111],"new":[47],"approach,":[48],"Fast":[49],"ROtary":[50],"Spatial":[52],"ACquisition":[53],"(FRONSAC)":[54],"imaging,":[55],"where":[56],"provide":[60],"small":[62],"rotating":[63],"perturbation":[64],"standard":[66],"linear":[67],"trajectories.":[68],"While":[69],"FRONSAC":[70,82,95,130,144],"greatly":[72],"improves":[73],"image":[74,141],"quality,":[75],"at":[76],"highest":[78],"accelerations":[79],"or":[80],"weakest":[81],"fields,":[83],"some":[84],"undersampling":[85],"artifacts":[86,91],"remain.":[87],"However,":[88],"under-sampling":[90],"that":[92,135],"occur":[93],"with":[94,143],"are":[97],"relatively":[98],"incoherent":[99],"well":[101],"suited":[102],"compressed":[105],"sensing":[106],"(CS)":[107],"reconstruction.":[108],"CS":[109],"provides":[110],"sparsity-promoting":[112],"convex":[113],"strategy":[114],"reconstruct":[116],"images":[117],"from":[118],"highly":[119],"undersampled":[120],"datasets.":[121],"The":[122],"work":[123],"here":[125],"combines":[126],"benefits":[128],"CS.":[132],"Simulations":[133],"illustrate":[134],"this":[136],"combination":[137],"can":[138],"further":[139],"improve":[140],"reconstruction":[142],"gradients":[145],"low":[147],"amplitudes":[148],"frequencies.":[150]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2016-06-24T00:00:00"}
