{"id":"https://openalex.org/W2153896334","doi":"https://doi.org/10.1109/icassp.2009.4959608","title":"Voxel selection in fMRI data analysis: A sparse representation method","display_name":"Voxel selection in fMRI data analysis: A sparse representation method","publication_year":2009,"publication_date":"2009-04-01","ids":{"openalex":"https://openalex.org/W2153896334","doi":"https://doi.org/10.1109/icassp.2009.4959608","mag":"2153896334"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2009.4959608","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2009.4959608","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Acoustics, Speech and Signal 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/A5100672536","display_name":"Yuanqing Li","orcid":"https://orcid.org/0000-0003-4288-5591"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuanqing Li","raw_affiliation_strings":["School of Automation, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110615211","display_name":"Zhuliang Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuliang Yu","raw_affiliation_strings":["School of Automation, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054748102","display_name":"Praneeth Namburi","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Praneeth Namburi","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031778999","display_name":"Cuntai Guan","orcid":"https://orcid.org/0000-0002-0872-3276"},"institutions":[{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Cuntai Guan","raw_affiliation_strings":["Institute for Infocomm Research, Singapore"],"affiliations":[{"raw_affiliation_string":"Institute for Infocomm Research, Singapore","institution_ids":["https://openalex.org/I3005327000"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100672536"],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.18849051,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"413","last_page":"416"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9973999857902527,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.8499268889427185},{"id":"https://openalex.org/keywords/statistical-parametric-mapping","display_name":"Statistical parametric mapping","score":0.6982888579368591},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6938150525093079},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6696735620498657},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.665075421333313},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.5585892200469971},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5369728803634644},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4179367125034332},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2514685094356537},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14828792214393616},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.08331584930419922}],"concepts":[{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.8499268889427185},{"id":"https://openalex.org/C39313694","wikidata":"https://www.wikidata.org/wiki/Q2940624","display_name":"Statistical parametric mapping","level":3,"score":0.6982888579368591},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6938150525093079},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6696735620498657},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.665075421333313},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.5585892200469971},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5369728803634644},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4179367125034332},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2514685094356537},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14828792214393616},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.08331584930419922},{"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":1,"locations":[{"id":"doi:10.1109/icassp.2009.4959608","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2009.4959608","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Acoustics, Speech and Signal Processing","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":13,"referenced_works":["https://openalex.org/W2099151709","https://openalex.org/W2105454037","https://openalex.org/W2106664807","https://openalex.org/W2112532472","https://openalex.org/W2115729631","https://openalex.org/W2116649573","https://openalex.org/W2120954952","https://openalex.org/W2135046866","https://openalex.org/W2154332973","https://openalex.org/W2172136399","https://openalex.org/W2949112253","https://openalex.org/W4235239134","https://openalex.org/W6685514809"],"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/W2119508653","https://openalex.org/W2399123545","https://openalex.org/W2129529516","https://openalex.org/W2361802826"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"an":[3],"iterative":[4],"sparse":[5,23],"representation-based":[6],"algorithmfor":[7],"voxel":[8,39,114],"selection":[9],"in":[10],"functionalmagnetic":[11],"resonance":[12],"imaging":[13],"(fMRI)":[14],"data.":[15],"The":[16],"output":[17],"of":[18,26,30,36,51,86],"the":[19,28,34,49,63,76,80,84,87],"algorithm":[20,53,61],"is":[21],"a":[22],"weight":[24],"vector,":[25],"which":[27,78],"magnitude":[29],"each":[31],"entry":[32],"represents":[33],"significance":[35],"its":[37,56],"corresponding":[38],"with":[40,90],"respect":[41],"to":[42,62,83],"mental":[43],"tasks":[44,85],"or":[45],"stimulus.":[46],"To":[47],"demonstrate":[48],"validity":[50],"our":[52,108],"and":[54,104],"illustrate":[55],"application,":[57],"we":[58],"apply":[59],"this":[60],"Pittsburgh":[64],"Brain":[65],"Activity":[66],"Interpretation":[67],"Competition":[68],"(PBAIC)":[69],"2007":[70],"fMRI":[71],"data":[72],"set":[73],"for":[74,113],"selecting":[75],"voxels":[77],"are":[79],"most":[81],"relevant":[82],"subjects.":[88],"Compared":[89],"three":[91],"baseline":[92],"methods,":[93],"general":[94],"linear":[95],"model":[96],"(GLM)-based":[97],"statistical":[98],"parametric":[99],"mapping":[100],"(SPM),":[101],"correlation":[102],"method":[103,109],"mutual":[105],"information":[106],"method,":[107],"shows":[110],"satisfactory":[111],"performance":[112],"selection.":[115]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
