{"id":"https://openalex.org/W2017863681","doi":"https://doi.org/10.1109/dicta.2012.6411710","title":"Automatic Detection of Arterial Voxels in Dynamic Contrast-Enhanced MR Images of the Brain","display_name":"Automatic Detection of Arterial Voxels in Dynamic Contrast-Enhanced MR Images of the Brain","publication_year":2012,"publication_date":"2012-12-01","ids":{"openalex":"https://openalex.org/W2017863681","doi":"https://doi.org/10.1109/dicta.2012.6411710","mag":"2017863681"},"language":"en","primary_location":{"id":"doi:10.1109/dicta.2012.6411710","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2012.6411710","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 International Conference on Digital Image Computing Techniques and Applications (DICTA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5042143932","display_name":"Sze Liang Stanley Chan","orcid":null},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Sze Liang Stanley Chan","raw_affiliation_strings":["University of Queensland, Brisbane, QLD, AU"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Queensland, Brisbane, QLD, AU","institution_ids":["https://openalex.org/I165143802"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110237168","display_name":"Yaniv Gal","orcid":null},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yaniv Gal","raw_affiliation_strings":["School of ITEE, The University of Queensland, Queensland, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of ITEE, The University of Queensland, Queensland, Australia","institution_ids":["https://openalex.org/I165143802"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I165143802"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.14564369,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9994000196456909,"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":0.9994000196456909,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9991999864578247,"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"}},{"id":"https://openalex.org/T10816","display_name":"Cerebrovascular and Carotid Artery Diseases","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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":0.7916180491447449},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.6882859468460083},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.546602725982666},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5032264590263367},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5017945766448975},{"id":"https://openalex.org/keywords/dynamic-contrast","display_name":"Dynamic contrast","score":0.42755216360092163},{"id":"https://openalex.org/keywords/biomedical-engineering","display_name":"Biomedical engineering","score":0.3983049690723419},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.2802530527114868},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.2118012011051178},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.12893855571746826}],"concepts":[{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.7916180491447449},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.6882859468460083},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.546602725982666},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5032264590263367},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5017945766448975},{"id":"https://openalex.org/C2994142346","wikidata":"https://www.wikidata.org/wiki/Q353268","display_name":"Dynamic contrast","level":3,"score":0.42755216360092163},{"id":"https://openalex.org/C136229726","wikidata":"https://www.wikidata.org/wiki/Q327092","display_name":"Biomedical engineering","level":1,"score":0.3983049690723419},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.2802530527114868},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.2118012011051178},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.12893855571746826}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/dicta.2012.6411710","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2012.6411710","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 International Conference on Digital Image Computing Techniques and Applications (DICTA)","raw_type":"proceedings-article"},{"id":"pmh:oai:espace.library.uq.edu.au:UQ:293624","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306402388","display_name":"Queensland's institutional digital repository (The University of Queensland)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I165143802","host_organization_name":"The University of Queensland","host_organization_lineage":["https://openalex.org/I165143802"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.8299999833106995}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W615648920","https://openalex.org/W1512148629","https://openalex.org/W1863759425","https://openalex.org/W1985834308","https://openalex.org/W1995046979","https://openalex.org/W1997611659","https://openalex.org/W2075069409","https://openalex.org/W2078237160","https://openalex.org/W2108610949","https://openalex.org/W2119555472","https://openalex.org/W2129534965","https://openalex.org/W2132549764","https://openalex.org/W2155653793","https://openalex.org/W2185178261","https://openalex.org/W2330562688","https://openalex.org/W4241709221","https://openalex.org/W6639110210","https://openalex.org/W6679367408","https://openalex.org/W6686396477"],"related_works":["https://openalex.org/W3027020613","https://openalex.org/W2016533837","https://openalex.org/W3167885074","https://openalex.org/W2892386716","https://openalex.org/W4306164210","https://openalex.org/W1998563493","https://openalex.org/W4313316311","https://openalex.org/W4362608745","https://openalex.org/W2383143032","https://openalex.org/W4385556094"],"abstract_inverted_index":{"Arterial":[0],"input":[1],"function":[2],"(AIF)":[3],"is":[4,28,103],"important":[5],"for":[6,62,151],"the":[7,14,29,34,37,63,71,96,101,120,135,139,143,159],"determination":[8],"of":[9,16,20,39,44,65,70,78,100,109,117,126,134,154,158],"cerebral":[10],"blood":[11],"flow":[12],"and":[13,80,123],"analysis":[15],"related":[17],"disease.":[18],"Detection":[19],"artery":[21,66],"voxels":[22,67,94],"in":[23,32,68,89,95,115,124,156],"dynamic":[24],"contrast-enhanced":[25],"(DCE)":[26],"MRI":[27],"key":[30],"challenge":[31],"estimating":[33],"AIF.":[35,131],"In":[36,52],"presence":[38],"tumour":[40],"tissue,":[41],"automatic":[42],"detection":[43,64],"arteries":[45],"becomes":[46],"as":[47,148],"even":[48],"more":[49],"challenging":[50],"task.":[51],"this":[53],"paper":[54],"we":[55],"propose":[56],"a":[57,76,85,149],"supervised":[58],"machine-learning":[59],"based":[60],"method":[61,74,102,141],"DCE-MRI":[69,107,157],"brain.":[72,160],"The":[73,98,132],"utilises":[75],"set":[77],"kinetic":[79],"local":[81],"structural":[82],"features":[83],"with":[84,111,128],"logistic":[86],"regression":[87],"classifier":[88],"order":[90],"to":[91,145],"detect":[92],"arterial":[93],"image.":[97],"performance":[99],"evaluated":[104],"on":[105],"11":[106],"datasets,":[108],"patients":[110],"diagnosed":[112],"brain":[113],"cancer,":[114],"terms":[116,125],"area":[118],"under":[119],"ROC":[121],"curve":[122],"correlation":[127],"an":[129],"ideal":[130],"results":[133],"evaluation":[136],"suggest":[137],"that":[138],"proposed":[140],"has":[142],"potential":[144],"be":[146],"used":[147],"tool":[150],"accurate":[152],"estimation":[153],"AIF":[155]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
