{"id":"https://openalex.org/W3133061553","doi":"https://doi.org/10.1117/12.2581011","title":"3-D multitask deep neural networks for collateral imaging from dynamic susceptibility contrast-enhanced magnetic resonance perfusion","display_name":"3-D multitask deep neural networks for collateral imaging from dynamic susceptibility contrast-enhanced magnetic resonance perfusion","publication_year":2021,"publication_date":"2021-02-12","ids":{"openalex":"https://openalex.org/W3133061553","doi":"https://doi.org/10.1117/12.2581011","mag":"3133061553"},"language":"en","primary_location":{"id":"doi:10.1117/12.2581011","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2581011","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2021: Computer-Aided Diagnosis","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/A5058990791","display_name":"Hoang Long Le","orcid":"https://orcid.org/0000-0001-6289-4941"},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hoang Long Le","raw_affiliation_strings":["Sejong Univ. (Korea, Republic of)"],"affiliations":[{"raw_affiliation_string":"Sejong Univ. (Korea, Republic of)","institution_ids":["https://openalex.org/I28777354"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101455200","display_name":"Yejin Jeon","orcid":"https://orcid.org/0000-0002-0077-9232"},"institutions":[{"id":"https://openalex.org/I138925566","display_name":"Ewha Womans University","ror":"https://ror.org/053fp5c05","country_code":"KR","type":"education","lineage":["https://openalex.org/I138925566"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yejin Jeon","raw_affiliation_strings":["Ewha Womans Univ. (Korea, Republic of)"],"affiliations":[{"raw_affiliation_string":"Ewha Womans Univ. (Korea, Republic of)","institution_ids":["https://openalex.org/I138925566"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006166728","display_name":"Hong Gee Roh","orcid":"https://orcid.org/0000-0003-0227-0971"},"institutions":[{"id":"https://openalex.org/I24062138","display_name":"Konkuk University","ror":"https://ror.org/025h1m602","country_code":"KR","type":"education","lineage":["https://openalex.org/I24062138"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hong Gee Roh","raw_affiliation_strings":["Konkuk Univ. (Korea, Republic of)"],"affiliations":[{"raw_affiliation_string":"Konkuk Univ. (Korea, Republic of)","institution_ids":["https://openalex.org/I24062138"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059650144","display_name":"Hyun Jeong Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I87111246","display_name":"Catholic University of Korea","ror":"https://ror.org/01fpnj063","country_code":"KR","type":"education","lineage":["https://openalex.org/I87111246"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyun Jeong Kim","raw_affiliation_strings":["The Catholic Univ. of Korea (Korea, Republic of)"],"affiliations":[{"raw_affiliation_string":"The Catholic Univ. of Korea (Korea, Republic of)","institution_ids":["https://openalex.org/I87111246"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036627754","display_name":"Jin Tae Kwak","orcid":"https://orcid.org/0000-0003-0287-4097"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin Tae Kwak","raw_affiliation_strings":["Korea Univ. (Korea, Republic of)"],"affiliations":[{"raw_affiliation_string":"Korea Univ. (Korea, Republic of)","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5058990791"],"corresponding_institution_ids":["https://openalex.org/I28777354"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.02470983,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"70","last_page":"70"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9991000294685364,"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":0.9991000294685364,"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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9950000047683716,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10227","display_name":"Acute Ischemic Stroke Management","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.6620009541511536},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6515289545059204},{"id":"https://openalex.org/keywords/magnetic-resonance-angiography","display_name":"Magnetic resonance angiography","score":0.5148617029190063},{"id":"https://openalex.org/keywords/dynamic-contrast","display_name":"Dynamic contrast","score":0.5089612007141113},{"id":"https://openalex.org/keywords/susceptibility-weighted-imaging","display_name":"Susceptibility weighted imaging","score":0.4978935718536377},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.4876517057418823},{"id":"https://openalex.org/keywords/collateral","display_name":"Collateral","score":0.47493770718574524},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.4690663814544678},{"id":"https://openalex.org/keywords/perfusion","display_name":"Perfusion","score":0.4564847946166992},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.45638516545295715},{"id":"https://openalex.org/keywords/perfusion-scanning","display_name":"Perfusion scanning","score":0.4347481429576874},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.4134156405925751},{"id":"https://openalex.org/keywords/stroke","display_name":"Stroke (engine)","score":0.41221609711647034},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40192461013793945},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3994086980819702},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.36011144518852234}],"concepts":[{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.6620009541511536},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6515289545059204},{"id":"https://openalex.org/C2778212899","wikidata":"https://www.wikidata.org/wiki/Q907325","display_name":"Magnetic resonance angiography","level":3,"score":0.5148617029190063},{"id":"https://openalex.org/C2994142346","wikidata":"https://www.wikidata.org/wiki/Q353268","display_name":"Dynamic contrast","level":3,"score":0.5089612007141113},{"id":"https://openalex.org/C16246696","wikidata":"https://www.wikidata.org/wiki/Q15282184","display_name":"Susceptibility weighted imaging","level":3,"score":0.4978935718536377},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.4876517057418823},{"id":"https://openalex.org/C2777910564","wikidata":"https://www.wikidata.org/wiki/Q694563","display_name":"Collateral","level":2,"score":0.47493770718574524},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.4690663814544678},{"id":"https://openalex.org/C146957229","wikidata":"https://www.wikidata.org/wiki/Q1266915","display_name":"Perfusion","level":2,"score":0.4564847946166992},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.45638516545295715},{"id":"https://openalex.org/C135691158","wikidata":"https://www.wikidata.org/wiki/Q7168308","display_name":"Perfusion scanning","level":3,"score":0.4347481429576874},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.4134156405925751},{"id":"https://openalex.org/C2780645631","wikidata":"https://www.wikidata.org/wiki/Q671554","display_name":"Stroke (engine)","level":2,"score":0.41221609711647034},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40192461013793945},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3994086980819702},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.36011144518852234},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2581011","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2581011","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2021: Computer-Aided Diagnosis","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8399999737739563,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3124626177","https://openalex.org/W1545046617","https://openalex.org/W1494925915","https://openalex.org/W4243562399","https://openalex.org/W3125787423","https://openalex.org/W3121982030","https://openalex.org/W2495941813","https://openalex.org/W3121410239","https://openalex.org/W1711502999","https://openalex.org/W2096819301"],"abstract_inverted_index":{"Acute":[0],"ischemic":[1],"stroke":[2],"(AIS)":[3],"is":[4,99],"not":[5],"only":[6],"a":[7,14,30,47],"common":[8],"cause":[9,16],"of":[10,17,81,165,174,176],"disability":[11],"but":[12],"also":[13],"leading":[15],"mortality":[18],"worldwide.":[19],"Recent":[20],"studies":[21],"have":[22],"shown":[23],"that":[24,63,155],"the":[25,38,42,93,115,151,156,163,170],"collateral":[26,69,97,166],"status":[27,98,167],"could":[28,159],"play":[29],"vital":[31],"role":[32],"in":[33,102,161],"assessing":[34],"AIS":[35,83,144],"and":[36,50,67,85,106,109,112,135,145,168,172],"determining":[37],"treatment":[39],"options":[40],"for":[41,54],"patients.":[43],"Herein,":[44],"we":[45],"propose":[46],"joint":[48],"regression":[49],"ordinal":[51],"learning":[52],"approach":[53],"AIS,":[55],"built":[56],"upon":[57],"3-D":[58],"deep":[59],"convolutional":[60],"neural":[61],"networks,":[62],"facilitates":[64],"an":[65],"automated":[66],"objective":[68],"imaging":[70],"from":[71],"dynamic":[72],"susceptibility":[73],"contrast-enhanced":[74],"magnetic":[75],"resonance":[76],"perfusion":[77],"(DSC-MRP).":[78],"DSC-MRP":[79],"images":[80],"159":[82],"subjects":[84,88,147],"186":[86],"healthy":[87,146],"are":[89,148],"employed":[90],"to":[91],"evaluate":[92],"proposed":[94,119,157],"approach.":[95],"The":[96,118,140],"manually":[100],"assessed":[101],"arterial,":[103],"capillary,":[104],"early":[105],"late":[107],"venous,":[108],"delay":[110],"phases":[111],"served":[113],"as":[114],"ground":[116],"truth.":[117],"method,":[120],"on":[121],"average,":[122],"obtained":[123],"0.901":[124],"squared":[125],"correlation":[126],"coefficient,":[127],"0.063":[128],"mean":[129],"absolute":[130],"error,":[131],"0.945":[132],"Tanimoto":[133],"measure,":[134],"0.933":[136],"structural":[137],"similarity":[138],"index.":[139],"quantitative":[141],"results":[142,153],"between":[143],"comparable.":[149],"Overall,":[150],"experimental":[152],"suggest":[154],"network":[158],"aid":[160],"automating":[162],"evaluation":[164],"enhancing":[169],"quality":[171],"yield":[173],"diagnosis":[175],"AIS.":[177]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}