{"id":"https://openalex.org/W2990057444","doi":"https://doi.org/10.1109/tmi.2019.2953901","title":"Efficient DCE-MRI Parameter and Uncertainty Estimation Using a Neural Network","display_name":"Efficient DCE-MRI Parameter and Uncertainty Estimation Using a Neural Network","publication_year":2019,"publication_date":"2019-11-26","ids":{"openalex":"https://openalex.org/W2990057444","doi":"https://doi.org/10.1109/tmi.2019.2953901","mag":"2990057444","pmid":"https://pubmed.ncbi.nlm.nih.gov/31794389"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2019.2953901","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tmi.2019.2953901","pdf_url":"https://ieeexplore.ieee.org/ielx7/42/9084068/08913635.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ieeexplore.ieee.org/ielx7/42/9084068/08913635.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5091255758","display_name":"Yannick Bliesener","orcid":"https://orcid.org/0000-0001-5436-1918"},"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":true,"raw_author_name":"Yannick Bliesener","raw_affiliation_strings":["Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, USA"],"affiliations":[{"raw_affiliation_string":"Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087706805","display_name":"Jay Acharya","orcid":"https://orcid.org/0000-0003-0873-0836"},"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":"Jay Acharya","raw_affiliation_strings":["Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, USA"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049543768","display_name":"Krishna S. Nayak","orcid":"https://orcid.org/0000-0001-5735-3550"},"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":"Krishna S. Nayak","raw_affiliation_strings":["Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, USA"],"affiliations":[{"raw_affiliation_string":"Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, USA","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5091255758"],"corresponding_institution_ids":["https://openalex.org/I1174212"],"apc_list":null,"apc_paid":null,"fwci":1.3706,"has_fulltext":true,"cited_by_count":29,"citation_normalized_percentile":{"value":0.82056897,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"39","issue":"5","first_page":"1712","last_page":"1723"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11885","display_name":"MRI in cancer diagnosis","score":1.0,"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/T11885","display_name":"MRI in cancer diagnosis","score":1.0,"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":0.9997000098228455,"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/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.9993000030517578,"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/voxel","display_name":"Voxel","score":0.7189897298812866},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5525408983230591},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5427936911582947},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.5425494313240051},{"id":"https://openalex.org/keywords/tracer","display_name":"TRACER","score":0.5208645462989807},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.42693373560905457},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4015005826950073},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3736385405063629},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3471505641937256},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1663881242275238}],"concepts":[{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.7189897298812866},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5525408983230591},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5427936911582947},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.5425494313240051},{"id":"https://openalex.org/C2778863792","wikidata":"https://www.wikidata.org/wiki/Q16909918","display_name":"TRACER","level":2,"score":0.5208645462989807},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.42693373560905457},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4015005826950073},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3736385405063629},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3471505641937256},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1663881242275238},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C185544564","wikidata":"https://www.wikidata.org/wiki/Q81197","display_name":"Nuclear physics","level":1,"score":0.0}],"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":"D000465","descriptor_name":"Algorithms","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":true},{"descriptor_ui":"D003287","descriptor_name":"Contrast Media","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003287","descriptor_name":"Contrast Media","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003287","descriptor_name":"Contrast Media","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"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":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D035501","descriptor_name":"Uncertainty","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D035501","descriptor_name":"Uncertainty","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D035501","descriptor_name":"Uncertainty","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D035501","descriptor_name":"Uncertainty","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1109/tmi.2019.2953901","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tmi.2019.2953901","pdf_url":"https://ieeexplore.ieee.org/ielx7/42/9084068/08913635.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},{"id":"pmid:31794389","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31794389","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:pubmedcentral.nih.gov:8887912","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8887912","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Trans Med Imaging","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1109/tmi.2019.2953901","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tmi.2019.2953901","pdf_url":"https://ieeexplore.ieee.org/ielx7/42/9084068/08913635.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4914663422","display_name":null,"funder_award_id":"R33-CA225400","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G8467997473","display_name":null,"funder_award_id":"R33-CA225400","funder_id":"https://openalex.org/F4320337351","funder_display_name":"National Cancer Institute"}],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337351","display_name":"National Cancer Institute","ror":"https://ror.org/040gcmg81"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2990057444.pdf","grobid_xml":"https://content.openalex.org/works/W2990057444.grobid-xml"},"referenced_works_count":67,"referenced_works":["https://openalex.org/W1506806321","https://openalex.org/W1522301498","https://openalex.org/W1760807988","https://openalex.org/W1775388337","https://openalex.org/W1913208704","https://openalex.org/W1959608418","https://openalex.org/W1963913232","https://openalex.org/W1966244775","https://openalex.org/W1971933336","https://openalex.org/W1974910032","https://openalex.org/W1982425190","https://openalex.org/W1992155932","https://openalex.org/W1993908838","https://openalex.org/W2000133863","https://openalex.org/W2001122120","https://openalex.org/W2009828098","https://openalex.org/W2017863681","https://openalex.org/W2024554845","https://openalex.org/W2032558189","https://openalex.org/W2032558547","https://openalex.org/W2040032797","https://openalex.org/W2045753892","https://openalex.org/W2049171359","https://openalex.org/W2064219797","https://openalex.org/W2065877493","https://openalex.org/W2066037527","https://openalex.org/W2070772485","https://openalex.org/W2073981577","https://openalex.org/W2084824769","https://openalex.org/W2089513130","https://openalex.org/W2094259943","https://openalex.org/W2100495367","https://openalex.org/W2101482993","https://openalex.org/W2105775163","https://openalex.org/W2109834560","https://openalex.org/W2112728443","https://openalex.org/W2120340025","https://openalex.org/W2122378596","https://openalex.org/W2129443736","https://openalex.org/W2133946415","https://openalex.org/W2140101310","https://openalex.org/W2142585416","https://openalex.org/W2155751421","https://openalex.org/W2167234030","https://openalex.org/W2168127946","https://openalex.org/W2198312848","https://openalex.org/W2289088667","https://openalex.org/W2290554571","https://openalex.org/W2318686907","https://openalex.org/W2398484313","https://openalex.org/W2401690196","https://openalex.org/W2526275343","https://openalex.org/W2550323446","https://openalex.org/W2577801124","https://openalex.org/W2584809905","https://openalex.org/W2769772619","https://openalex.org/W2799913653","https://openalex.org/W2893810171","https://openalex.org/W2907448641","https://openalex.org/W2908796452","https://openalex.org/W2922479016","https://openalex.org/W2964121744","https://openalex.org/W3103052966","https://openalex.org/W4212948410","https://openalex.org/W4293052541","https://openalex.org/W6631190155","https://openalex.org/W6640963894"],"related_works":["https://openalex.org/W2001254114","https://openalex.org/W2045362891","https://openalex.org/W2018752697","https://openalex.org/W2054546918","https://openalex.org/W2090152913","https://openalex.org/W1966069390","https://openalex.org/W1998782558","https://openalex.org/W2080122327","https://openalex.org/W1970746087","https://openalex.org/W2278340220"],"abstract_inverted_index":{"Quantitative":[0],"DCE-MRI":[1],"provides":[2],"voxel-wise":[3],"estimates":[4],"of":[5,14,25,50,60,83,154],"tracer-kinetic":[6,51,62,84,109,138,182],"parameters":[7,52],"that":[8],"are":[9,87,93],"valuable":[10],"in":[11,124,126,163,175,179],"the":[12,61,78,96,103,152,180],"assessment":[13],"health":[15],"and":[16,36,53,71,92,99,121,146],"disease.":[17],"These":[18],"maps":[19],"suffer":[20],"from":[21,160],"many":[22],"known":[23],"sources":[24],"variability.":[26],"This":[27,169],"variability":[28],"is":[29,37,170],"expensive":[30],"to":[31,57,76,95,106,157],"compute":[32],"using":[33],"current":[34],"methods,":[35],"typically":[38],"not":[39],"reported.":[40],"Here,":[41],"we":[42],"demonstrate":[43,102,151],"a":[44,73,127],"novel":[45],"approach":[46,156],"for":[47,89],"simultaneous":[48],"estimation":[49],"their":[54],"uncertainty":[55],"due":[56],"intrinsic":[58],"characteristics":[59],"model,":[63],"with":[64,116,137],"very":[65],"low":[66],"computation":[67],"time.":[68,168],"We":[69,101,111,149],"train":[70],"use":[72],"neural":[74],"network":[75],"estimate":[77],"approximate":[79],"joint":[80],"posterior":[81],"distribution":[82],"parameters.":[85],"Uncertainties":[86],"estimated":[88],"each":[90],"voxel":[91],"specific":[94],"patient,":[97],"exam,":[98],"lesion.":[100],"methods'":[104],"ability":[105],"produce":[107],"accurate":[108],"maps.":[110],"compare":[112],"predicted":[113,132],"parameter":[114,133,139],"ranges":[115,134,140],"uncertainties":[117],"introduced":[118],"by":[119,122,172],"noise":[120,144],"differences":[123],"post-processing":[125],"digital":[128],"reference":[129],"object.":[130],"The":[131],"correlate":[135],"well":[136],"observed":[141],"across":[142],"different":[143],"realizations":[145],"regression":[147],"algorithms.":[148],"also":[150],"value":[153],"this":[155],"differentiate":[158],"significant":[159],"insignificant":[161],"changes":[162],"brain":[164],"tumor":[165],"pharmacokinetics":[166],"over":[167],"achieved":[171],"enforcing":[173],"consistency":[174],"resolving":[176],"model":[177],"singularities":[178],"applied":[181],"model.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}