{"id":"https://openalex.org/W2903730443","doi":"https://doi.org/10.23919/spa.2018.8563431","title":"Automated determination of arterial input function in DCE-MR images of the kidney","display_name":"Automated determination of arterial input function in DCE-MR images of the kidney","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2903730443","doi":"https://doi.org/10.23919/spa.2018.8563431","mag":"2903730443"},"language":"en","primary_location":{"id":"doi:10.23919/spa.2018.8563431","is_oa":false,"landing_page_url":"https://doi.org/10.23919/spa.2018.8563431","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5047509459","display_name":"Artur Klepaczko","orcid":"https://orcid.org/0000-0003-4045-5870"},"institutions":[{"id":"https://openalex.org/I188884621","display_name":"Lodz University of Technology","ror":"https://ror.org/00s8fpf52","country_code":"PL","type":"education","lineage":["https://openalex.org/I188884621"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Artur Klepaczko","raw_affiliation_strings":["Lodz University of Technology, Institute of Electronics, Lodz, Poland"],"affiliations":[{"raw_affiliation_string":"Lodz University of Technology, Institute of Electronics, Lodz, Poland","institution_ids":["https://openalex.org/I188884621"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041964950","display_name":"Martyna Muszelska","orcid":null},"institutions":[{"id":"https://openalex.org/I188884621","display_name":"Lodz University of Technology","ror":"https://ror.org/00s8fpf52","country_code":"PL","type":"education","lineage":["https://openalex.org/I188884621"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Martyna Muszelska","raw_affiliation_strings":["Lodz University of Technology, Institute of Electronics, Lodz, Poland"],"affiliations":[{"raw_affiliation_string":"Lodz University of Technology, Institute of Electronics, Lodz, Poland","institution_ids":["https://openalex.org/I188884621"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044027361","display_name":"Eli Eikefjord","orcid":"https://orcid.org/0000-0003-0067-8180"},"institutions":[{"id":"https://openalex.org/I2800740805","display_name":"Haukeland University Hospital","ror":"https://ror.org/03np4e098","country_code":"NO","type":"healthcare","lineage":["https://openalex.org/I2800740805"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Eli Eikefjord","raw_affiliation_strings":["Department of Radiology, Haukeland University Hospital, Bergen, Norway"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, Haukeland University Hospital, Bergen, Norway","institution_ids":["https://openalex.org/I2800740805"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057350858","display_name":"Jarle R\u00f8rvik","orcid":"https://orcid.org/0000-0003-1853-1670"},"institutions":[{"id":"https://openalex.org/I4432739","display_name":"University of Bergen","ror":"https://ror.org/03zga2b32","country_code":"NO","type":"education","lineage":["https://openalex.org/I4432739"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Jarle Rorvik","raw_affiliation_strings":["Department of Clinical Medicine, University of Bergen, Bergen, Norway"],"affiliations":[{"raw_affiliation_string":"Department of Clinical Medicine, University of Bergen, Bergen, Norway","institution_ids":["https://openalex.org/I4432739"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060325633","display_name":"Arvid Lundervold","orcid":"https://orcid.org/0000-0002-0032-4182"},"institutions":[{"id":"https://openalex.org/I4432739","display_name":"University of Bergen","ror":"https://ror.org/03zga2b32","country_code":"NO","type":"education","lineage":["https://openalex.org/I4432739"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Arvid Lundervold","raw_affiliation_strings":["Department of Biomedicine, University of Bergen, Bergen, Norway"],"affiliations":[{"raw_affiliation_string":"Department of Biomedicine, University of Bergen, Bergen, Norway","institution_ids":["https://openalex.org/I4432739"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5047509459"],"corresponding_institution_ids":["https://openalex.org/I188884621"],"apc_list":null,"apc_paid":null,"fwci":0.1768,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.58106739,"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":"280","last_page":"285"},"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":0.9995999932289124,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9980000257492065,"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":0.7929974794387817},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6545698642730713},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5485062599182129},{"id":"https://openalex.org/keywords/perfusion","display_name":"Perfusion","score":0.4979383945465088},{"id":"https://openalex.org/keywords/descending-aorta","display_name":"Descending aorta","score":0.4942772388458252},{"id":"https://openalex.org/keywords/dynamic-contrast-enhanced-mri","display_name":"Dynamic contrast-enhanced MRI","score":0.4742507040500641},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37853357195854187},{"id":"https://openalex.org/keywords/aorta","display_name":"Aorta","score":0.3432565927505493},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.2483654022216797},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.24088534712791443},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1947610080242157},{"id":"https://openalex.org/keywords/cardiology","display_name":"Cardiology","score":0.1261204481124878}],"concepts":[{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.7929974794387817},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6545698642730713},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5485062599182129},{"id":"https://openalex.org/C146957229","wikidata":"https://www.wikidata.org/wiki/Q1266915","display_name":"Perfusion","level":2,"score":0.4979383945465088},{"id":"https://openalex.org/C2780663194","wikidata":"https://www.wikidata.org/wiki/Q3270170","display_name":"Descending aorta","level":3,"score":0.4942772388458252},{"id":"https://openalex.org/C41727105","wikidata":"https://www.wikidata.org/wiki/Q17009718","display_name":"Dynamic contrast-enhanced MRI","level":3,"score":0.4742507040500641},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37853357195854187},{"id":"https://openalex.org/C2779980429","wikidata":"https://www.wikidata.org/wiki/Q101004","display_name":"Aorta","level":2,"score":0.3432565927505493},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.2483654022216797},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.24088534712791443},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1947610080242157},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.1261204481124878}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/spa.2018.8563431","is_oa":false,"landing_page_url":"https://doi.org/10.23919/spa.2018.8563431","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.6899999976158142}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1962314142","https://openalex.org/W1989117065","https://openalex.org/W2013478821","https://openalex.org/W2025630096","https://openalex.org/W2026616100","https://openalex.org/W2036936638","https://openalex.org/W2058209392","https://openalex.org/W2093461708","https://openalex.org/W2125671174","https://openalex.org/W2140198969","https://openalex.org/W2150806080","https://openalex.org/W2152910484"],"related_works":["https://openalex.org/W2413481960","https://openalex.org/W2022154546","https://openalex.org/W3043270608","https://openalex.org/W2329191057","https://openalex.org/W2325618378","https://openalex.org/W3211835263","https://openalex.org/W2085104584","https://openalex.org/W2182910414","https://openalex.org/W2396152760","https://openalex.org/W2056087498"],"abstract_inverted_index":{"This":[0],"paper":[1],"concerns":[2],"the":[3,11,23,45,51,54,66,70,82,90,97,122,135,154],"problem":[4],"of":[5,17,25,31,53,65,75,92,107,140,153],"estimating":[6],"renal":[7],"perfusion":[8,18,156],"based":[9],"on":[10],"Dynamic":[12],"Contrast":[13],"Enhanced":[14],"MRI.":[15],"Quantification":[16],"parameters":[19,157],"is":[20,41,69,77],"possible":[21],"by":[22],"means":[24],"pharmacokinetic":[26],"modeling.":[27],"Several":[28],"mathematical":[29],"formulations":[30],"PK":[32],"models":[33],"have":[34],"been":[35],"proposed.":[36],"In":[37,63],"any":[38],"case,":[39],"it":[40,68],"important":[42],"to":[43,85,115,121,127],"determine":[44,86],"so-called":[46],"arterial":[47],"input":[48],"function,":[49],"i.e.":[50],"time-course":[52],"contrast":[55],"agent":[56],"bolus":[57],"in":[58,96,151],"a":[59,93,105],"main":[60],"feeding":[61],"artery.":[62],"case":[64],"kidney":[67],"descending":[71,123],"aorta.":[72],"Usually,":[73],"determination":[74],"AIF":[76],"performed":[78,143],"manually.":[79],"We":[80],"propose":[81],"automatic":[83],"procedure":[84],"AIF,":[87],"thus":[88],"reducing":[89],"involvement":[91],"human":[94],"observer":[95],"image":[98,108],"processing":[99,109],"pipeline.":[100],"Our":[101],"proposed":[102],"method":[103,142],"uses":[104],"combination":[106],"and":[110,125],"machine":[111],"learning":[112],"algorithms":[113],"firstly":[114],"identify":[116],"all":[117],"voxels":[118,130],"potentially":[119],"belonging":[120],"aorta":[124],"secondly":[126],"select":[128],"those":[129],"which":[131],"are":[132],"free":[133],"from":[134],"inflow":[136],"artifact.":[137],"The":[138],"tests":[139],"our":[141],"for":[144],"10":[145],"DCE-MRI":[146],"datasets":[147],"show":[148],"its":[149],"effectiveness":[150],"terms":[152],"resulting":[155],"measurements.":[158]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}