{"id":"https://openalex.org/W1867048779","doi":"https://doi.org/10.1109/tmi.2008.2007326","title":"Quantitative Analysis of Dynamic Contrast-Enhanced MR Images Based on Bayesian P-Splines","display_name":"Quantitative Analysis of Dynamic Contrast-Enhanced MR Images Based on Bayesian P-Splines","publication_year":2008,"publication_date":"2008-11-06","ids":{"openalex":"https://openalex.org/W1867048779","doi":"https://doi.org/10.1109/tmi.2008.2007326","mag":"1867048779","pmid":"https://pubmed.ncbi.nlm.nih.gov/19272996"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2008.2007326","is_oa":false,"landing_page_url":"http://doi.org/10.1109/tmi.2008.2007326","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/0801.4065","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"V.J. Schmid","orcid":null},"institutions":[{"id":"https://openalex.org/I4210109636","display_name":"NIHR Imperial Biomedical Research Centre","ror":"https://ror.org/01kmhx639","country_code":"GB","type":"facility","lineage":["https://openalex.org/I34931013","https://openalex.org/I4210109636"]},{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"V.J. Schmid","raw_affiliation_strings":["Institute of Biomedical Engineering, Imperial College, SW7 2AZ London, UK"],"affiliations":[{"raw_affiliation_string":"Institute of Biomedical Engineering, Imperial College, SW7 2AZ London, UK","institution_ids":["https://openalex.org/I4210109636","https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":null,"display_name":"B. Whitcher","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"B. Whitcher","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"A.R. Padhani","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"A.R. Padhani","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Guang-Zhong Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guang-Zhong Yang","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210109636","https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":1.2365,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.79545283,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"28","issue":"6","first_page":"789","last_page":"798"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11885","display_name":"MRI in cancer diagnosis","score":0.855400025844574,"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":0.855400025844574,"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/T11829","display_name":"Mathematical Biology Tumor Growth","score":0.0203000009059906,"subfield":{"id":"https://openalex.org/subfields/2611","display_name":"Modeling and Simulation"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.014100000262260437,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.6585000157356262},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5683000087738037},{"id":"https://openalex.org/keywords/spline","display_name":"Spline (mechanical)","score":0.5648000240325928},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5220000147819519},{"id":"https://openalex.org/keywords/smoothing-spline","display_name":"Smoothing spline","score":0.5196999907493591},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.4699000120162964},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.4564000070095062},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.41260001063346863},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.3959999978542328},{"id":"https://openalex.org/keywords/basis-function","display_name":"Basis function","score":0.37720000743865967}],"concepts":[{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.6585000157356262},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5683000087738037},{"id":"https://openalex.org/C10390562","wikidata":"https://www.wikidata.org/wiki/Q581809","display_name":"Spline (mechanical)","level":2,"score":0.5648000240325928},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5594000220298767},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5220000147819519},{"id":"https://openalex.org/C107457265","wikidata":"https://www.wikidata.org/wiki/Q7546460","display_name":"Smoothing spline","level":4,"score":0.5196999907493591},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.4699000120162964},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4602999985218048},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.4564000070095062},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4250999987125397},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.41260001063346863},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.3959999978542328},{"id":"https://openalex.org/C5917680","wikidata":"https://www.wikidata.org/wiki/Q2621825","display_name":"Basis function","level":2,"score":0.37720000743865967},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.365200012922287},{"id":"https://openalex.org/C174576160","wikidata":"https://www.wikidata.org/wiki/Q1183700","display_name":"Deconvolution","level":2,"score":0.321399986743927},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.31439998745918274},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.3142000138759613},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3034000098705292},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.2980000078678131},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.2906000018119812},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.28780001401901245},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.2854999899864197},{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.2847000062465668},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2842000126838684},{"id":"https://openalex.org/C68022304","wikidata":"https://www.wikidata.org/wiki/Q842217","display_name":"Bayes estimator","level":3,"score":0.27970001101493835},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.27709999680519104},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2655999958515167},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.2646999955177307},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.26249998807907104},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.25929999351501465}],"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":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001940","descriptor_name":"Breast","qualifier_ui":"Q000473","qualifier_name":"pathology","is_major_topic":false},{"descriptor_ui":"D001940","descriptor_name":"Breast","qualifier_ui":"Q000473","qualifier_name":"pathology","is_major_topic":false},{"descriptor_ui":"D001940","descriptor_name":"Breast","qualifier_ui":"Q000473","qualifier_name":"pathology","is_major_topic":false},{"descriptor_ui":"D001943","descriptor_name":"Breast Neoplasms","qualifier_ui":"Q000473","qualifier_name":"pathology","is_major_topic":false},{"descriptor_ui":"D001943","descriptor_name":"Breast Neoplasms","qualifier_ui":"Q000473","qualifier_name":"pathology","is_major_topic":false},{"descriptor_ui":"D001943","descriptor_name":"Breast Neoplasms","qualifier_ui":"Q000473","qualifier_name":"pathology","is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003287","descriptor_name":"Contrast Media","qualifier_ui":"Q000493","qualifier_name":"pharmacokinetics","is_major_topic":false},{"descriptor_ui":"D003287","descriptor_name":"Contrast Media","qualifier_ui":"Q000493","qualifier_name":"pharmacokinetics","is_major_topic":false},{"descriptor_ui":"D003287","descriptor_name":"Contrast Media","qualifier_ui":"Q000493","qualifier_name":"pharmacokinetics","is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","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":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007700","descriptor_name":"Kinetics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007700","descriptor_name":"Kinetics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007700","descriptor_name":"Kinetics","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":"D008390","descriptor_name":"Markov Chains","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008390","descriptor_name":"Markov Chains","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008390","descriptor_name":"Markov Chains","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009010","descriptor_name":"Monte Carlo Method","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009010","descriptor_name":"Monte Carlo Method","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009010","descriptor_name":"Monte Carlo Method","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013997","descriptor_name":"Time Factors","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013997","descriptor_name":"Time Factors","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013997","descriptor_name":"Time Factors","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1109/tmi.2008.2007326","is_oa":false,"landing_page_url":"http://doi.org/10.1109/tmi.2008.2007326","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:19272996","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/19272996","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:arXiv.org:0801.4065","is_oa":true,"landing_page_url":"http://arxiv.org/abs/0801.4065","pdf_url":"https://arxiv.org/pdf/0801.4065","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"},{"id":"pmh:oai:westminsterresearch.westminster.ac.uk:w057v","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2008.2007326","pdf_url":null,"source":{"id":"https://openalex.org/S4306400277","display_name":"WestminsterResearch (University of Westminster)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I94951947","host_organization_name":"University of Westminster","host_organization_lineage":["https://openalex.org/I94951947"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:0801.4065","is_oa":true,"landing_page_url":"http://arxiv.org/abs/0801.4065","pdf_url":"https://arxiv.org/pdf/0801.4065","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":40,"referenced_works":["https://openalex.org/W47949175","https://openalex.org/W150588681","https://openalex.org/W1505178423","https://openalex.org/W1912628714","https://openalex.org/W1968036288","https://openalex.org/W1980526942","https://openalex.org/W1981168627","https://openalex.org/W1982536610","https://openalex.org/W1990420052","https://openalex.org/W1993307911","https://openalex.org/W2008843339","https://openalex.org/W2015480546","https://openalex.org/W2017917156","https://openalex.org/W2021539460","https://openalex.org/W2022876326","https://openalex.org/W2024071340","https://openalex.org/W2030003406","https://openalex.org/W2035837210","https://openalex.org/W2042098439","https://openalex.org/W2048387155","https://openalex.org/W2049171359","https://openalex.org/W2064219797","https://openalex.org/W2072246398","https://openalex.org/W2078284051","https://openalex.org/W2092566521","https://openalex.org/W2099303263","https://openalex.org/W2108610949","https://openalex.org/W2112407618","https://openalex.org/W2112728443","https://openalex.org/W2113501324","https://openalex.org/W2119047368","https://openalex.org/W2133127239","https://openalex.org/W2145906985","https://openalex.org/W2149783293","https://openalex.org/W2150374672","https://openalex.org/W2155751421","https://openalex.org/W2156346018","https://openalex.org/W2167943787","https://openalex.org/W2596469055","https://openalex.org/W4241292274"],"related_works":[],"abstract_inverted_index":{"Dynamic":[0],"contrast-enhanced":[1],"magnetic":[2],"resonance":[3],"imaging":[4],"(DCE-MRI)":[5],"is":[6,68,97,158],"an":[7,27],"important":[8],"tool":[9],"for":[10],"detecting":[11],"subtle":[12],"kinetic":[13,45,126],"changes":[14],"in":[15,155],"cancerous":[16],"tissue.":[17],"Quantitative":[18],"analysis":[19],"of":[20,26,37,43,53,64,74,102,143,148],"DCE-MRI":[21],"typically":[22],"involves":[23],"the":[24,38,44,51,54,65,72,75,95,133,141,149],"convolution":[25],"arterial":[28],"input":[29],"function":[30],"(AIF)":[31],"with":[32,99,152],"a":[33,88,100,106],"nonlinear":[34,55],"pharmacokinetic":[35],"model":[36,46,56,76],"contrast":[39,144],"agent":[40],"concentration.":[41],"Parameters":[42],"are":[47],"biologically":[48],"meaningful,":[49],"but":[50],"optimization":[52,66],"has":[57,122],"significant":[58],"computational":[59],"issues.":[60],"In":[61],"practice,":[62],"convergence":[63],"algorithm":[67],"not":[69],"guaranteed":[70],"and":[71,154],"accuracy":[73],"fitting":[77],"may":[78],"be":[79,130],"compromised.":[80],"To":[81],"overcome":[82],"these":[83],"problems,":[84],"this":[85],"paper":[86],"proposes":[87],"semi-parametric":[89],"penalized":[90,117],"spline":[91,118],"smoothing":[92,112],"approach,":[93],"where":[94],"AIF":[96],"convolved":[98],"set":[101],"B-splines":[103],"to":[104],"produce":[105],"design":[107],"matrix":[108],"using":[109],"locally":[110],"adaptive":[111],"parameters":[113],"based":[114],"on":[115],"Bayesian":[116],"models":[119],"(P-splines).":[120],"It":[121],"been":[123],"shown":[124],"that":[125],"parameter":[127],"estimation":[128],"can":[129],"obtained":[131],"from":[132],"resulting":[134],"deconvolved":[135],"response":[136],"function,":[137],"which":[138],"also":[139],"includes":[140],"onset":[142],"enhancement.":[145],"Detailed":[146],"validation":[147],"method,":[150],"both":[151],"simulated":[153],"vivo":[156],"data,":[157],"provided.":[159]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":8},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":4}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2016-06-24T00:00:00"}