{"id":"https://openalex.org/W1995580022","doi":"https://doi.org/10.1109/icip.2010.5653354","title":"A Bayesian model selection approach to fMRI activation detection","display_name":"A Bayesian model selection approach to fMRI activation detection","publication_year":2010,"publication_date":"2010-09-01","ids":{"openalex":"https://openalex.org/W1995580022","doi":"https://doi.org/10.1109/icip.2010.5653354","mag":"1995580022"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2010.5653354","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2010.5653354","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Conference on Image Processing","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/A5084681382","display_name":"Abd\u2010Krim Seghouane","orcid":"https://orcid.org/0000-0003-4619-734X"},"institutions":[{"id":"https://openalex.org/I118347636","display_name":"Australian National University","ror":"https://ror.org/019wvm592","country_code":"AU","type":"education","lineage":["https://openalex.org/I118347636"]},{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Abd-Krim Seghouane","raw_affiliation_strings":["National ICT Australia, Canberra Research Laboratory, College of Engineering and Computer Science, Australian National University, Canberra, Australia","National ICT Australia, Canberra Research Laboratory, The Australian National University, College of Engineering and Computer Science, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National ICT Australia, Canberra Research Laboratory, College of Engineering and Computer Science, Australian National University, Canberra, Australia","institution_ids":["https://openalex.org/I118347636","https://openalex.org/I42894916"]},{"raw_affiliation_string":"National ICT Australia, Canberra Research Laboratory, The Australian National University, College of Engineering and Computer Science, Australia","institution_ids":["https://openalex.org/I118347636"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090401556","display_name":"Ju Lynn Ong","orcid":"https://orcid.org/0000-0001-5115-4112"},"institutions":[{"id":"https://openalex.org/I118347636","display_name":"Australian National University","ror":"https://ror.org/019wvm592","country_code":"AU","type":"education","lineage":["https://openalex.org/I118347636"]},{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Ju Lynn Ong","raw_affiliation_strings":["National ICT Australia, Canberra Research Laboratory, College of Engineering and Computer Science, Australian National University, Canberra, Australia","National ICT Australia, Canberra Research Laboratory, The Australian National University, College of Engineering and Computer Science, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National ICT Australia, Canberra Research Laboratory, College of Engineering and Computer Science, Australian National University, Canberra, Australia","institution_ids":["https://openalex.org/I118347636","https://openalex.org/I42894916"]},{"raw_affiliation_string":"National ICT Australia, Canberra Research Laboratory, The Australian National University, College of Engineering and Computer Science, Australia","institution_ids":["https://openalex.org/I118347636"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7751,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.74236122,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"4401","last_page":"4404"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9995999932289124,"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"}},"topics":[{"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/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.7105545401573181},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6961624622344971},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6566640734672546},{"id":"https://openalex.org/keywords/statistical-parametric-mapping","display_name":"Statistical parametric mapping","score":0.635269045829773},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6135269403457642},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5730067491531372},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.545823872089386},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5074004530906677},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4736548662185669},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4607990086078644},{"id":"https://openalex.org/keywords/functional-magnetic-resonance-imaging","display_name":"Functional magnetic resonance imaging","score":0.4315233826637268},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.42508774995803833},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38922569155693054},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3736345171928406},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16558781266212463},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15611910820007324},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.09722942113876343},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.07371997833251953}],"concepts":[{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.7105545401573181},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6961624622344971},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6566640734672546},{"id":"https://openalex.org/C39313694","wikidata":"https://www.wikidata.org/wiki/Q2940624","display_name":"Statistical parametric mapping","level":3,"score":0.635269045829773},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6135269403457642},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5730067491531372},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.545823872089386},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5074004530906677},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4736548662185669},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4607990086078644},{"id":"https://openalex.org/C2779226451","wikidata":"https://www.wikidata.org/wiki/Q903809","display_name":"Functional magnetic resonance imaging","level":2,"score":0.4315233826637268},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.42508774995803833},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38922569155693054},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3736345171928406},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16558781266212463},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15611910820007324},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.09722942113876343},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.07371997833251953},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icip.2010.5653354","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2010.5653354","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Conference on Image Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:openresearch-repository.anu.edu.au:1885/62463","is_oa":false,"landing_page_url":"http://hdl.handle.net/1885/62463","pdf_url":null,"source":{"id":"https://openalex.org/S4306402539","display_name":"ANU Open Research (Australian National University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I118347636","host_organization_name":"Australian National University","host_organization_lineage":["https://openalex.org/I118347636"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of IEEE International Conference on Image Processing 2010","raw_type":"Conference paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W15567521","https://openalex.org/W1995466435","https://openalex.org/W1995605620","https://openalex.org/W2063237661","https://openalex.org/W2071714163","https://openalex.org/W2072200265","https://openalex.org/W2093366270","https://openalex.org/W2098892992","https://openalex.org/W2104134023","https://openalex.org/W2131556788","https://openalex.org/W2131751614","https://openalex.org/W2168175751","https://openalex.org/W2493977830","https://openalex.org/W3196620053","https://openalex.org/W4246845213"],"related_works":["https://openalex.org/W3027020613","https://openalex.org/W2327200162","https://openalex.org/W2119508653","https://openalex.org/W1977508323","https://openalex.org/W2129529516","https://openalex.org/W2781524617","https://openalex.org/W2152416379","https://openalex.org/W3032257994","https://openalex.org/W1987060659","https://openalex.org/W2042306781"],"abstract_inverted_index":{"A":[0,23],"fundamental":[1],"question":[2],"in":[3,31],"functional":[4],"MRI":[5],"(fMRI)":[6],"data":[7,33,55],"analysis":[8],"is":[9,34,38,66,94],"to":[10,19,49,82],"declare":[11],"pixels":[12,30],"either":[13],"activated":[14,29],"or":[15],"non-activated":[16],"with":[17,56],"respect":[18],"the":[20,42,45,50,74,88],"experimental":[21,98],"design.":[22],"new":[24],"statistical":[25],"test":[26,37,72],"for":[27,68],"detecting":[28],"fMRI":[32,52,90],"proposed.":[35],"The":[36,62,85],"based":[39],"on":[40,96],"comparing":[41],"dimension":[43],"of":[44,76,87],"parametric":[46],"models":[47],"fitted":[48],"voxels":[51],"time":[53],"series":[54],"and":[57],"without":[58],"controlled":[59],"activation-baseline":[60],"pattern.":[61],"Bayesian":[63],"information":[64],"criterion,":[65],"used":[67],"this":[69],"comparison.":[70],"This":[71],"has":[73],"advantage":[75],"not":[77],"requiring":[78],"any":[79],"user-specified":[80],"threshold":[81],"be":[83],"estimated.":[84],"effectiveness":[86],"proposed":[89],"activation":[91],"detection":[92],"method":[93],"illustrated":[95],"real":[97],"data.":[99]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}