{"id":"https://openalex.org/W2148154121","doi":"https://doi.org/10.1109/isbi.2004.1398676","title":"Reversible jump Markov chain Monte Carlo signal detection in functional neuroimaging analysis","display_name":"Reversible jump Markov chain Monte Carlo signal detection in functional neuroimaging analysis","publication_year":2005,"publication_date":"2005-04-12","ids":{"openalex":"https://openalex.org/W2148154121","doi":"https://doi.org/10.1109/isbi.2004.1398676","mag":"2148154121"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2004.1398676","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2004.1398676","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (IEEE Cat No. 04EX821)","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/A5102839062","display_name":"Ana Luki\u0107","orcid":"https://orcid.org/0000-0002-0662-4856"},"institutions":[{"id":"https://openalex.org/I180949307","display_name":"Illinois Institute of Technology","ror":"https://ror.org/037t3ry66","country_code":"US","type":"education","lineage":["https://openalex.org/I180949307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"A.S. Lukic","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL, USA","institution_ids":["https://openalex.org/I180949307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043182454","display_name":"Miles N. Wernick","orcid":null},"institutions":[{"id":"https://openalex.org/I180949307","display_name":"Illinois Institute of Technology","ror":"https://ror.org/037t3ry66","country_code":"US","type":"education","lineage":["https://openalex.org/I180949307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"M.N. Wernick","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL, USA","institution_ids":["https://openalex.org/I180949307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026606753","display_name":"N.P. Galatsanos","orcid":null},"institutions":[{"id":"https://openalex.org/I194019607","display_name":"University of Ioannina","ror":"https://ror.org/01qg3j183","country_code":"GR","type":"education","lineage":["https://openalex.org/I194019607"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"N.P. Galatsanos","raw_affiliation_strings":["University of Ioannina (UoI), Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Ioannina (UoI), Greece","institution_ids":["https://openalex.org/I194019607"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048510347","display_name":"Yongyi Yang","orcid":"https://orcid.org/0000-0003-3564-3260"},"institutions":[{"id":"https://openalex.org/I180949307","display_name":"Illinois Institute of Technology","ror":"https://ror.org/037t3ry66","country_code":"US","type":"education","lineage":["https://openalex.org/I180949307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yongyi Yang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL, USA","institution_ids":["https://openalex.org/I180949307"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009298184","display_name":"Stephen C. Strother","orcid":"https://orcid.org/0000-0002-3198-217X"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]},{"id":"https://openalex.org/I4210140408","display_name":"Minneapolis VA Medical Center","ror":"https://ror.org/032b8d361","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1322918889","https://openalex.org/I2799886695","https://openalex.org/I4210117246","https://openalex.org/I4210117924","https://openalex.org/I4210140408"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"S.C. Strother","raw_affiliation_strings":["VA Medical Center, University of Minnesota, Minneapolis, MN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"VA Medical Center, University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516","https://openalex.org/I4210140408"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"868","last_page":"871"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.998199999332428,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.998199999332428,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"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/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9919999837875366,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reversible-jump-markov-chain-monte-carlo","display_name":"Reversible-jump Markov chain Monte Carlo","score":0.9594532251358032},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.7093124389648438},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.63959801197052},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.6097120642662048},{"id":"https://openalex.org/keywords/superposition-principle","display_name":"Superposition principle","score":0.5583634376525879},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5266444683074951},{"id":"https://openalex.org/keywords/neuroimaging","display_name":"Neuroimaging","score":0.5156049132347107},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.5150017738342285},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.513127863407135},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.5059258341789246},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.49776604771614075},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.4836622178554535},{"id":"https://openalex.org/keywords/jump","display_name":"Jump","score":0.44346368312835693},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.43229788541793823},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.41196009516716003},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24166899919509888},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.20677313208580017},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.17806407809257507},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.17367541790008545},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.09779319167137146}],"concepts":[{"id":"https://openalex.org/C2780591659","wikidata":"https://www.wikidata.org/wiki/Q17083869","display_name":"Reversible-jump Markov chain Monte Carlo","level":4,"score":0.9594532251358032},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.7093124389648438},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.63959801197052},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.6097120642662048},{"id":"https://openalex.org/C27753989","wikidata":"https://www.wikidata.org/wiki/Q284885","display_name":"Superposition principle","level":2,"score":0.5583634376525879},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5266444683074951},{"id":"https://openalex.org/C58693492","wikidata":"https://www.wikidata.org/wiki/Q551875","display_name":"Neuroimaging","level":2,"score":0.5156049132347107},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.5150017738342285},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.513127863407135},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.5059258341789246},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.49776604771614075},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.4836622178554535},{"id":"https://openalex.org/C2780695682","wikidata":"https://www.wikidata.org/wiki/Q4005959","display_name":"Jump","level":2,"score":0.44346368312835693},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.43229788541793823},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.41196009516716003},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24166899919509888},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.20677313208580017},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.17806407809257507},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.17367541790008545},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.09779319167137146},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2004.1398676","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2004.1398676","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (IEEE Cat No. 04EX821)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1982891217","https://openalex.org/W1985093013","https://openalex.org/W2024986101","https://openalex.org/W2025472057","https://openalex.org/W2045200995","https://openalex.org/W2055309705","https://openalex.org/W2070115712","https://openalex.org/W2106706098","https://openalex.org/W2166048062","https://openalex.org/W4231923904","https://openalex.org/W4292403327"],"related_works":["https://openalex.org/W2953867467","https://openalex.org/W3151507825","https://openalex.org/W2001857141","https://openalex.org/W2951072873","https://openalex.org/W1554021357","https://openalex.org/W2146317212","https://openalex.org/W2493909506","https://openalex.org/W71678127","https://openalex.org/W2112913028","https://openalex.org/W4205763938"],"abstract_inverted_index":{"We":[0,21,44,104],"propose":[1],"a":[2,16,27,56,67],"new":[3],"signal-detection":[4],"approach":[5],"for":[6],"detecting":[7],"brain":[8],"activations":[9],"from":[10],"PET":[11],"or":[12],"fMRI":[13,120],"images":[14],"in":[15,89],"two-state":[17],"(\"on-off')":[18],"neuroimaging":[19],"study.":[20],"model":[22,91],"the":[23,46,62,90,93,106,109,123],"activation":[24,96],"pattern":[25],"as":[26],"superposition":[28],"of":[29,33,38,48,76,85,95,108],"an":[30],"unknown":[31,39,86],"number":[32,47,94],"circular":[34],"spatial":[35],"basis":[36],"functions":[37,50],"position,":[40],"size,":[41],"and":[42,51,117],"amplitude.":[43],"determine":[45],"these":[49],"their":[52],"parameters":[53],"by":[54],"maximum":[55],"posteriori":[57],"(MAP)":[58],"estimation.":[59],"To":[60],"maximize":[61],"posterior":[63],"distribution":[64],"we":[65],"use":[66],"reversible-jump":[68],"Markov-chain":[69],"Monte-Carlo":[70],"(RJMCMC)":[71],"algorithm.":[72],"The":[73],"main":[74],"advantage":[75],"RJMCMC":[77],"is":[78],"that":[79],"it":[80],"can":[81],"estimate":[82],"parameter":[83],"vectors":[84],"length.":[87],"Thus,":[88],"used":[92],"sites":[97],"does":[98],"not":[99],"need":[100],"to":[101],"be":[102],"known.":[103],"evaluate":[105],"performance":[107],"algorithm":[110],"on":[111,118],"synthetic":[112],"data":[113,121],"using":[114,122],"ROC":[115],"curves":[116],"real":[119],"NPAIRSresampling":[124],"framework.":[125]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
