{"id":"https://openalex.org/W2901062761","doi":"https://doi.org/10.1109/tmi.2019.2900585","title":"Understanding the Combined Effect of ${k}$ -Space Undersampling and Transient States Excitation in MR Fingerprinting Reconstructions","display_name":"Understanding the Combined Effect of ${k}$ -Space Undersampling and Transient States Excitation in MR Fingerprinting Reconstructions","publication_year":2019,"publication_date":"2019-02-22","ids":{"openalex":"https://openalex.org/W2901062761","doi":"https://doi.org/10.1109/tmi.2019.2900585","mag":"2901062761","pmid":"https://pubmed.ncbi.nlm.nih.gov/30802852"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2019.2900585","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2019.2900585","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/1811.07564","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Christiaan C. Stolk","orcid":"https://orcid.org/0000-0002-0944-3428"},"institutions":[{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Christiaan C. Stolk","raw_affiliation_strings":["Korteweg-de Vries Institute for Mathematics, University of Amsterdam, Amsterdam, The Netherlands"],"raw_orcid":"https://orcid.org/0000-0002-0944-3428","affiliations":[{"raw_affiliation_string":"Korteweg-de Vries Institute for Mathematics, University of Amsterdam, Amsterdam, The Netherlands","institution_ids":["https://openalex.org/I887064364"]}]},{"author_position":"last","author":{"id":null,"display_name":"Alessandro Sbrizzi","orcid":"https://orcid.org/0000-0003-3276-4542"},"institutions":[{"id":"https://openalex.org/I3018483916","display_name":"University Medical Center Utrecht","ror":"https://ror.org/0575yy874","country_code":"NL","type":"healthcare","lineage":["https://openalex.org/I3018483916"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Alessandro Sbrizzi","raw_affiliation_strings":["Department of Radiology, University Medical Center, Utrecht, Utrecht, CX, The Netherlands"],"raw_orcid":"https://orcid.org/0000-0003-3276-4542","affiliations":[{"raw_affiliation_string":"Department of Radiology, University Medical Center, Utrecht, Utrecht, CX, The Netherlands","institution_ids":["https://openalex.org/I3018483916"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I887064364"],"apc_list":null,"apc_paid":null,"fwci":3.1717,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.91396036,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"38","issue":"10","first_page":"2445","last_page":"2455"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9362999796867371,"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":0.9362999796867371,"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/T12381","display_name":"Electron Spin Resonance Studies","score":0.010599999688565731,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"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/T11279","display_name":"Lanthanide and Transition Metal Complexes","score":0.007799999788403511,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/undersampling","display_name":"Undersampling","score":0.9711999893188477},{"id":"https://openalex.org/keywords/excitation","display_name":"Excitation","score":0.6740999817848206},{"id":"https://openalex.org/keywords/transient","display_name":"Transient (computer programming)","score":0.5717999935150146},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5408999919891357},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.5171999931335449},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.42089998722076416},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38179999589920044}],"concepts":[{"id":"https://openalex.org/C136536468","wikidata":"https://www.wikidata.org/wiki/Q1225894","display_name":"Undersampling","level":2,"score":0.9711999893188477},{"id":"https://openalex.org/C83581075","wikidata":"https://www.wikidata.org/wiki/Q1361503","display_name":"Excitation","level":2,"score":0.6740999817848206},{"id":"https://openalex.org/C2780799671","wikidata":"https://www.wikidata.org/wiki/Q17087362","display_name":"Transient (computer programming)","level":2,"score":0.5717999935150146},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5647000074386597},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5408999919891357},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5249999761581421},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5171999931335449},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4740000069141388},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.42089998722076416},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38179999589920044},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.38100001215934753},{"id":"https://openalex.org/C46141821","wikidata":"https://www.wikidata.org/wiki/Q209402","display_name":"Nuclear magnetic resonance","level":1,"score":0.37689998745918274},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.30390000343322754},{"id":"https://openalex.org/C182155053","wikidata":"https://www.wikidata.org/wiki/Q7259682","display_name":"Pulse sequence","level":2,"score":0.298799991607666},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.29820001125335693},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.28349998593330383},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.2761000096797943},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.2727000117301941},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.2639000117778778},{"id":"https://openalex.org/C139210041","wikidata":"https://www.wikidata.org/wiki/Q2145840","display_name":"Resonance (particle physics)","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.2567000091075897},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.2533000111579895},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.25130000710487366},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.25060001015663147}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","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":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","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},{"descriptor_ui":"D019047","descriptor_name":"Phantoms, Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019047","descriptor_name":"Phantoms, Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019047","descriptor_name":"Phantoms, Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1109/tmi.2019.2900585","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2019.2900585","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:30802852","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30802852","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:dare.uva.nl:openaire_cris_publications/9b75f2e6-448d-4fcf-8c3a-b0dc681ecfde","is_oa":false,"landing_page_url":"https://handle.uba.uva.nl/personal/pure/en/publications/understanding-the-combined-effect-of-kspace-undersampling-and-transient-states-excitation-in-mr-fingerprinting-reconstructions(9b75f2e6-448d-4fcf-8c3a-b0dc681ecfde).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400088","display_name":"UvA-DARE (University of Amsterdam)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I887064364","host_organization_name":"University of Amsterdam","host_organization_lineage":["https://openalex.org/I887064364"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Stolk, C C & Sbrizzi, A 2019, 'Understanding the Combined Effect of k -Space Undersampling and Transient States Excitation in MR Fingerprinting Reconstructions', IEEE Transactions on Medical Imaging, vol. 38, no. 10, pp. 2445-2455. https://doi.org/10.1109/TMI.2019.2900585","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:arXiv.org:1811.07564","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1811.07564","pdf_url":"https://arxiv.org/pdf/1811.07564","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:1811.07564","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1811.07564","pdf_url":"https://arxiv.org/pdf/1811.07564","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1510815927","https://openalex.org/W1867572349","https://openalex.org/W2012300893","https://openalex.org/W2029816571","https://openalex.org/W2035808554","https://openalex.org/W2061708033","https://openalex.org/W2099944953","https://openalex.org/W2120575449","https://openalex.org/W2140804420","https://openalex.org/W2144288697","https://openalex.org/W2263221359","https://openalex.org/W2324009747","https://openalex.org/W2330484003","https://openalex.org/W2510165053","https://openalex.org/W2511213994","https://openalex.org/W2576603068","https://openalex.org/W2591549471","https://openalex.org/W2613279989"],"related_works":[],"abstract_inverted_index":{"Magnetic":[0],"resonance":[1],"fingerprinting":[2],"(MRF)":[3],"is":[4,24,71],"able":[5],"to":[6,85,131],"estimate":[7],"multiple":[8],"quantitative":[9],"tissue":[10],"parameters":[11],"from":[12],"a":[13,68,106],"relatively":[14],"short":[15],"acquisition.":[16],"The":[17,117],"main":[18],"characteristic":[19],"of":[20,28,57,109],"an":[21],"MRF":[22,100,134],"sequence":[23,101],"the":[25,40,54,62,76,81,86,96,133],"simultaneous":[26],"application":[27],"1)":[29],"transient":[30],"states":[31],"excitation":[32,79],"and":[33,80],"2)":[34],"highly":[35],"undersampled":[36],"k":[37,82],"-space.":[38],"Despite":[39],"promising":[41],"empirical":[42],"results":[43],"obtained":[44,121],"with":[45],"MRF,":[46],"no":[47],"work":[48],"has":[49],"appeared":[50],"that":[51,73],"formally":[52],"describes":[53],"combined":[55],"impact":[56],"these":[58],"two":[59],"aspects":[60],"on":[61],"reconstruction":[63,89],"accuracy.":[64],"In":[65],"this":[66,125],"paper,":[67],"mathematical":[69],"model":[70],"derived":[72],"directly":[74],"relates":[75],"time-varying":[77],"RF":[78],"-space":[83],"sampling":[84],"spatially":[87],"dependent":[88],"errors.":[90],"A":[91],"subsequent":[92],"in-depth":[93],"analysis":[94],"identifies":[95],"mechanisms":[97],"by":[98],"which":[99,122],"properties":[102],"affect":[103],"accuracy,":[104],"providing":[105],"formal":[107],"explanation":[108],"several":[110],"empirically":[111],"observed":[112],"or":[113],"intuitively":[114],"understood":[115],"facts.":[116],"new":[118],"insights":[119],"are":[120],"show":[123],"how":[124],"analytical":[126],"framework":[127],"could":[128],"be":[129],"used":[130],"improve":[132],"protocol.":[135]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":3}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2018-11-29T00:00:00"}