{"id":"https://openalex.org/W1983913071","doi":"https://doi.org/10.1109/mmbia.2012.6164763","title":"A generalized correlation coefficient: Application to DTI and multi-fiber DTI","display_name":"A generalized correlation coefficient: Application to DTI and multi-fiber DTI","publication_year":2012,"publication_date":"2012-01-01","ids":{"openalex":"https://openalex.org/W1983913071","doi":"https://doi.org/10.1109/mmbia.2012.6164763","mag":"1983913071"},"language":"en","primary_location":{"id":"doi:10.1109/mmbia.2012.6164763","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmbia.2012.6164763","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Workshop on Mathematical Methods in Biomedical Image Analysis","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/A5074189635","display_name":"Maxime Taquet","orcid":"https://orcid.org/0000-0002-8987-952X"},"institutions":[{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]},{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]},{"id":"https://openalex.org/I95674353","display_name":"UCLouvain","ror":"https://ror.org/02495e989","country_code":"BE","type":"education","lineage":["https://openalex.org/I95674353"]}],"countries":["BE","US"],"is_corresponding":true,"raw_author_name":"Maxime Taquet","raw_affiliation_strings":["Computational Radiology Laboratory, Harvard Medical School, Boston, USA","ICTEAM Institute, Universit\u00e9 catholique de Louvain, Louvain-La-Neuve, Belgium"],"affiliations":[{"raw_affiliation_string":"Computational Radiology Laboratory, Harvard Medical School, Boston, USA","institution_ids":["https://openalex.org/I136199984","https://openalex.org/I111088046"]},{"raw_affiliation_string":"ICTEAM Institute, Universit\u00e9 catholique de Louvain, Louvain-La-Neuve, Belgium","institution_ids":["https://openalex.org/I95674353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015968689","display_name":"Beno\u0131\u0302t Macq","orcid":"https://orcid.org/0000-0002-7243-4778"},"institutions":[{"id":"https://openalex.org/I95674353","display_name":"UCLouvain","ror":"https://ror.org/02495e989","country_code":"BE","type":"education","lineage":["https://openalex.org/I95674353"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Benoit Macq","raw_affiliation_strings":["ICTEAM Institute, Universit\u00e9 catholique de Louvain, Louvain-La-Neuve, Belgium"],"affiliations":[{"raw_affiliation_string":"ICTEAM Institute, Universit\u00e9 catholique de Louvain, Louvain-La-Neuve, Belgium","institution_ids":["https://openalex.org/I95674353"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054913205","display_name":"Simon K. Warfield","orcid":"https://orcid.org/0000-0002-7659-3880"},"institutions":[{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]},{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Simon K. Warfield","raw_affiliation_strings":["Computational Radiology Laboratory, Harvard Medical School, Boston, USA"],"affiliations":[{"raw_affiliation_string":"Computational Radiology Laboratory, Harvard Medical School, Boston, USA","institution_ids":["https://openalex.org/I136199984","https://openalex.org/I111088046"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5074189635"],"corresponding_institution_ids":["https://openalex.org/I111088046","https://openalex.org/I136199984","https://openalex.org/I95674353"],"apc_list":null,"apc_paid":null,"fwci":1.2129,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.78788848,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"26","issue":null,"first_page":"9","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.996399998664856,"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/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.996399998664856,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9947999715805054,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9926000237464905,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.5341353416442871},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.41404345631599426},{"id":"https://openalex.org/keywords/diffusion-mri","display_name":"Diffusion MRI","score":0.4116244614124298},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.36055588722229004},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3001755177974701},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.22215384244918823},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.12831488251686096},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.08610600233078003},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.07086756825447083},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.0526677668094635}],"concepts":[{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.5341353416442871},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.41404345631599426},{"id":"https://openalex.org/C149550507","wikidata":"https://www.wikidata.org/wiki/Q899360","display_name":"Diffusion MRI","level":3,"score":0.4116244614124298},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.36055588722229004},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3001755177974701},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.22215384244918823},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.12831488251686096},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.08610600233078003},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.07086756825447083},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0526677668094635}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/mmbia.2012.6164763","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmbia.2012.6164763","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Workshop on Mathematical Methods in Biomedical Image Analysis","raw_type":"proceedings-article"},{"id":"pmh:oai:dial.uclouvain.be:boreal:136964","is_oa":false,"landing_page_url":"http://hdl.handle.net/2078.1/136964","pdf_url":null,"source":{"id":"https://openalex.org/S4306401902","display_name":"Digital Access to Libraries (Universit\u00e9 catholique de Louvain (UCL), l'Universit\u00e9 de Namur (UNamur) and the Universit\u00e9 Saint-Louis (USL-B))","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I95674353","host_organization_name":"UCLouvain","host_organization_lineage":["https://openalex.org/I95674353"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1526085390","https://openalex.org/W1555823621","https://openalex.org/W1564102252","https://openalex.org/W1575002547","https://openalex.org/W1598557217","https://openalex.org/W1819772690","https://openalex.org/W1949070191","https://openalex.org/W1968663451","https://openalex.org/W2009039636","https://openalex.org/W2042422178","https://openalex.org/W2080198834","https://openalex.org/W2094682431","https://openalex.org/W2100770901","https://openalex.org/W2109060361","https://openalex.org/W2135354879","https://openalex.org/W2164801701","https://openalex.org/W6634270568","https://openalex.org/W6635900159"],"related_works":["https://openalex.org/W2372194214","https://openalex.org/W3081640970","https://openalex.org/W4200439127","https://openalex.org/W2021013714","https://openalex.org/W2412250669","https://openalex.org/W2359856669","https://openalex.org/W2078603735","https://openalex.org/W1488551807","https://openalex.org/W2023979854","https://openalex.org/W2560331580"],"abstract_inverted_index":{"Multi-fiber":[0],"models":[1],"have":[2],"been":[3,25],"introduced":[4],"as":[5,87],"an":[6],"efficient":[7],"and":[8,66,93],"interpretable":[9],"way":[10],"of":[11,42,52,75,101],"representing":[12],"the":[13,53,60,76,80,99,102],"diffusion":[14,77],"signal":[15],"in":[16,31,40,79,104],"areas":[17,105],"with":[18,106],"crossing":[19,107],"fibers.":[20,108],"However,":[21],"no":[22],"metric":[23,89],"has":[24],"provided":[26],"to":[27,46],"use":[28,85],"multi-fiber":[29],"features":[30,97],"registration.":[32],"The":[33,69],"normalized":[34,61],"correlation":[35,62],"coefficient":[36,63],"is":[37],"commonly":[38],"used":[39],"registration":[41],"scalar":[43],"images":[44],"due":[45],"its":[47],"invariance":[48,71],"under":[49],"linear":[50,73],"transformations":[51,74],"intensities.":[54],"In":[55],"this":[56],"paper,":[57],"we":[58],"generalize":[59],"for":[64,90],"tensor":[65],"multi-tensor":[67,96],"images.":[68],"generalized":[70],"allows":[72],"eigenvalues":[78],"logarithmic":[81],"domain.":[82],"We":[83],"subsequently":[84],"it":[86],"a":[88],"block":[91],"matching":[92,103],"show":[94],"that":[95],"leverage":[98],"accuracy":[100]},"counts_by_year":[{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}