{"id":"https://openalex.org/W2535510318","doi":"https://doi.org/10.1109/embc.2016.7590737","title":"Optimal experiment design for magnetic resonance fingerprinting","display_name":"Optimal experiment design for magnetic resonance fingerprinting","publication_year":2016,"publication_date":"2016-08-01","ids":{"openalex":"https://openalex.org/W2535510318","doi":"https://doi.org/10.1109/embc.2016.7590737","mag":"2535510318","pmid":"https://pubmed.ncbi.nlm.nih.gov/28268369"},"language":"en","primary_location":{"id":"doi:10.1109/embc.2016.7590737","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2016.7590737","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5060182809","display_name":"Bo Zhao","orcid":"https://orcid.org/0000-0002-3475-8739"},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]},{"id":"https://openalex.org/I4210087915","display_name":"Massachusetts General Hospital","ror":"https://ror.org/002pd6e78","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210087915","https://openalex.org/I48633490"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bo Zhao","raw_affiliation_strings":["Massachusetts General Hospital, Harvard Medical School"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Massachusetts General Hospital, Harvard Medical School","institution_ids":["https://openalex.org/I136199984","https://openalex.org/I4210087915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031370363","display_name":"Justin P. Haldar","orcid":"https://orcid.org/0000-0002-1838-0211"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Justin P. Haldar","raw_affiliation_strings":["Ming Hsieh Department of Electrical Engineering, University of Southern California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ming Hsieh Department of Electrical Engineering, University of Southern California","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090829577","display_name":"Kawin Setsompop","orcid":"https://orcid.org/0000-0003-0455-7634"},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]},{"id":"https://openalex.org/I4210087915","display_name":"Massachusetts General Hospital","ror":"https://ror.org/002pd6e78","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210087915","https://openalex.org/I48633490"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kawin Setsompop","raw_affiliation_strings":["Massachusetts General Hospital, Harvard Medical School"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Massachusetts General Hospital, Harvard Medical School","institution_ids":["https://openalex.org/I136199984","https://openalex.org/I4210087915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005761034","display_name":"Lawrence L. Wald","orcid":"https://orcid.org/0000-0001-8278-6307"},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]},{"id":"https://openalex.org/I4210087915","display_name":"Massachusetts General Hospital","ror":"https://ror.org/002pd6e78","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210087915","https://openalex.org/I48633490"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lawrence L. Wald","raw_affiliation_strings":["Massachusetts General Hospital, Harvard Medical School"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Massachusetts General Hospital, Harvard Medical School","institution_ids":["https://openalex.org/I136199984","https://openalex.org/I4210087915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.5654,"has_fulltext":false,"cited_by_count":39,"citation_normalized_percentile":{"value":0.99097706,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"2016","issue":null,"first_page":"453","last_page":"456"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9932000041007996,"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":0.9932000041007996,"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/T11970","display_name":"Molecular Biology Techniques and Applications","score":0.9725000262260437,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10662","display_name":"Ultrasonics and Acoustic Wave Propagation","score":0.9641000032424927,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/estimator","display_name":"Estimator","score":0.6724088191986084},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.6127716302871704},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5598085522651672},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.552331268787384},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.5362733006477356},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5152154564857483},{"id":"https://openalex.org/keywords/cram\u00e9r\u2013rao-bound","display_name":"Cram\u00e9r\u2013Rao bound","score":0.48582789301872253},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.4723148047924042},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4522817134857178},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4243772625923157},{"id":"https://openalex.org/keywords/design-of-experiments","display_name":"Design of experiments","score":0.4198800027370453},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29467085003852844},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2944493293762207},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.26394757628440857}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6724088191986084},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.6127716302871704},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5598085522651672},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.552331268787384},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.5362733006477356},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5152154564857483},{"id":"https://openalex.org/C4978587","wikidata":"https://www.wikidata.org/wiki/Q1138810","display_name":"Cram\u00e9r\u2013Rao bound","level":3,"score":0.48582789301872253},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.4723148047924042},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4522817134857178},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4243772625923157},{"id":"https://openalex.org/C34559072","wikidata":"https://www.wikidata.org/wiki/Q2334061","display_name":"Design of experiments","level":2,"score":0.4198800027370453},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29467085003852844},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2944493293762207},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.26394757628440857},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"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},{"descriptor_ui":"D059629","descriptor_name":"Signal-To-Noise Ratio","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D059629","descriptor_name":"Signal-To-Noise Ratio","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D059629","descriptor_name":"Signal-To-Noise Ratio","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1109/embc.2016.7590737","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2016.7590737","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:28268369","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28268369","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":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":"Journal Article"},{"id":"pmh:oai:europepmc.org:4314331","is_oa":false,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5464426","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"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":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1109774327","display_name":null,"funder_award_id":"R24 MH106096","funder_id":"https://openalex.org/F4320337346","funder_display_name":"National Institute of Mental Health"},{"id":"https://openalex.org/G1243485958","display_name":null,"funder_award_id":"P41EB-015896","funder_id":"https://openalex.org/F4320337363","funder_display_name":"National Institute of Biomedical Imaging and Bioengineering"},{"id":"https://openalex.org/G1693937026","display_name":null,"funder_award_id":"R01EB017337","funder_id":"https://openalex.org/F4320337363","funder_display_name":"National Institute of Biomedical Imaging and Bioengineering"},{"id":"https://openalex.org/G2154169669","display_name":null,"funder_award_id":"U01MH093765.","funder_id":"https://openalex.org/F4320337346","funder_display_name":"National Institute of Mental Health"},{"id":"https://openalex.org/G3048631115","display_name":null,"funder_award_id":"R01NS089212","funder_id":"https://openalex.org/F4320337359","funder_display_name":"National Institute of Neurological Disorders and Stroke"},{"id":"https://openalex.org/G3447810086","display_name":null,"funder_award_id":"R01-EB017219","funder_id":"https://openalex.org/F4320337363","funder_display_name":"National Institute of Biomedical Imaging and Bioengineering"},{"id":"https://openalex.org/G483618622","display_name":null,"funder_award_id":"R00 EB012107","funder_id":"https://openalex.org/F4320337363","funder_display_name":"National Institute of Biomedical Imaging and Bioengineering"}],"funders":[{"id":"https://openalex.org/F4320337346","display_name":"National Institute of Mental Health","ror":"https://ror.org/04xeg9z08"},{"id":"https://openalex.org/F4320337359","display_name":"National Institute of Neurological Disorders and Stroke","ror":"https://ror.org/01s5ya894"},{"id":"https://openalex.org/F4320337363","display_name":"National Institute of Biomedical Imaging and Bioengineering","ror":"https://ror.org/00372qc85"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W242464784","https://openalex.org/W250076511","https://openalex.org/W1510815927","https://openalex.org/W1521875821","https://openalex.org/W1965392255","https://openalex.org/W1993011342","https://openalex.org/W2035808554","https://openalex.org/W2144288697","https://openalex.org/W2151500097","https://openalex.org/W2156195892","https://openalex.org/W2163641775","https://openalex.org/W2324009747"],"related_works":["https://openalex.org/W2585557503","https://openalex.org/W2169354510","https://openalex.org/W1967296369","https://openalex.org/W2057485678","https://openalex.org/W4389474210","https://openalex.org/W1971427935","https://openalex.org/W2014635939","https://openalex.org/W2073381184","https://openalex.org/W2470658235","https://openalex.org/W1952484348"],"abstract_inverted_index":{"Magnetic":[0],"resonance":[1],"(MR)":[2],"fingerprinting":[3,34,124],"is":[4,102],"an":[5,18,26,64,122],"emerging":[6],"quantitative":[7],"MR":[8,33,59,123],"imaging":[9],"technique":[10],"that":[11,86,110],"simultaneously":[12],"acquires":[13],"multiple":[14],"tissue":[15],"parameters":[16,79],"in":[17,118,129],"efficient":[19],"experiment.":[20,95],"In":[21],"this":[22],"work,":[23],"we":[24,38],"present":[25],"estimation-theoretic":[27],"framework":[28],"to":[29,54,73],"evaluate":[30],"and":[31,126],"design":[32,67],"experiments.":[35],"More":[36],"specifically,":[37],"derive":[39],"the":[40,48,71,88,93,99,111,119],"Cram\u00e9r-Rao":[41],"bound":[42,46],"(CRB),":[43],"a":[44,75],"lower":[45],"on":[47,70],"covariance":[49],"of":[50,77,92,98,121],"any":[51],"unbiased":[52],"estimator,":[53],"characterize":[55],"parameter":[56,130],"estimation":[57,131],"for":[58,115],"fingerprinting.":[60],"We":[61],"then":[62],"formulate":[63],"optimal":[65],"experiment":[66],"problem":[68],"based":[69],"CRB":[72],"choose":[74],"set":[76],"acquisition":[78],"(e.g.,":[80],"flip":[81],"angles":[82],"and/or":[83],"repetition":[84],"times)":[85],"maximizes":[87],"signal-to-noise":[89],"ratio":[90],"efficiency":[91],"resulting":[94],"The":[96],"utility":[97],"proposed":[100],"approach":[101],"validated":[103],"by":[104],"numerical":[105],"studies.":[106],"Representative":[107],"results":[108],"demonstrate":[109],"optimized":[112],"experiments":[113],"allow":[114],"substantial":[116,127],"reduction":[117],"length":[120],"acquisition,":[125],"improvement":[128],"performance.":[132]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}