{"id":"https://openalex.org/W2108280650","doi":"https://doi.org/10.1109/isbi.2006.1625036","title":"A Statistical Framework for DTI Segmentation","display_name":"A Statistical Framework for DTI Segmentation","publication_year":2006,"publication_date":"2006-05-25","ids":{"openalex":"https://openalex.org/W2108280650","doi":"https://doi.org/10.1109/isbi.2006.1625036","mag":"2108280650"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2006.1625036","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2006.1625036","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"3rd IEEE International Symposium on Biomedical Imaging: Macro to Nano, 2006.","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/A5114735669","display_name":"C. Lengler","orcid":null},"institutions":[{"id":"https://openalex.org/I1326498283","display_name":"Institut national de recherche en sciences et technologies du num\u00e9rique","ror":"https://ror.org/02kvxyf05","country_code":"FR","type":"government","lineage":["https://openalex.org/I1326498283"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"C. Lengler","raw_affiliation_strings":["INRIA, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"INRIA, France","institution_ids":["https://openalex.org/I1326498283"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067087969","display_name":"Mika\u00ebl Rousson","orcid":null},"institutions":[{"id":"https://openalex.org/I1325886976","display_name":"Siemens (Germany)","ror":"https://ror.org/059mq0909","country_code":"DE","type":"company","lineage":["https://openalex.org/I1325886976"]},{"id":"https://openalex.org/I4210137693","display_name":"Siemens (United States)","ror":"https://ror.org/04axb7e79","country_code":"US","type":"company","lineage":["https://openalex.org/I1325886976","https://openalex.org/I4210137693"]}],"countries":["DE","US"],"is_corresponding":false,"raw_author_name":"M. Rousson","raw_affiliation_strings":["Siemens AG Corporate Research and Development, Princeton, NJ, USA","[Siemens AG Corporate Research and Development, Princeton, NJ, USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Siemens AG Corporate Research and Development, Princeton, NJ, USA","institution_ids":["https://openalex.org/I4210137693"]},{"raw_affiliation_string":"[Siemens AG Corporate Research and Development, Princeton, NJ, USA]","institution_ids":["https://openalex.org/I1325886976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082632190","display_name":"Rachid Deriche","orcid":"https://orcid.org/0000-0002-4643-8417"},"institutions":[{"id":"https://openalex.org/I1326498283","display_name":"Institut national de recherche en sciences et technologies du num\u00e9rique","ror":"https://ror.org/02kvxyf05","country_code":"FR","type":"government","lineage":["https://openalex.org/I1326498283"]},{"id":"https://openalex.org/I4210115519","display_name":"Centre de Recherche en Informatique","ror":"https://ror.org/020cdve92","country_code":"FR","type":"facility","lineage":["https://openalex.org/I190752583","https://openalex.org/I2746051580","https://openalex.org/I4210091621","https://openalex.org/I4210115519","https://openalex.org/I70768539"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"R. Deriche","raw_affiliation_strings":["INRIA, Sophia-Antipolis, France","INRIA Institut National de Recherche en Informatique et en Automatique"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"INRIA, Sophia-Antipolis, France","institution_ids":["https://openalex.org/I1326498283"]},{"raw_affiliation_string":"INRIA Institut National de Recherche en Informatique et en Automatique","institution_ids":["https://openalex.org/I1326498283","https://openalex.org/I4210115519"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.2036,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.91190865,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"794","last_page":"797"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":1.0,"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":1.0,"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":0.9940000176429749,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.9778000116348267,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/diffusion-mri","display_name":"Diffusion MRI","score":0.6630547642707825},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.599398136138916},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.591289758682251},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5836082696914673},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5742725729942322},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5461434721946716},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5310141444206238},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5067735314369202},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.496559202671051},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.44724810123443604},{"id":"https://openalex.org/keywords/manifold","display_name":"Manifold (fluid mechanics)","score":0.4319131672382355},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.42362871766090393},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.4204053282737732},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.15875312685966492}],"concepts":[{"id":"https://openalex.org/C149550507","wikidata":"https://www.wikidata.org/wiki/Q899360","display_name":"Diffusion MRI","level":3,"score":0.6630547642707825},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.599398136138916},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.591289758682251},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5836082696914673},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5742725729942322},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5461434721946716},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5310141444206238},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5067735314369202},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.496559202671051},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.44724810123443604},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.4319131672382355},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.42362871766090393},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.4204053282737732},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.15875312685966492},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2006.1625036","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2006.1625036","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"3rd IEEE International Symposium on Biomedical Imaging: Macro to Nano, 2006.","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":23,"referenced_works":["https://openalex.org/W631955151","https://openalex.org/W1501540518","https://openalex.org/W1558431342","https://openalex.org/W1583399309","https://openalex.org/W1607885873","https://openalex.org/W1796159577","https://openalex.org/W1964802316","https://openalex.org/W1991113069","https://openalex.org/W2032236594","https://openalex.org/W2044562173","https://openalex.org/W2044981864","https://openalex.org/W2063282370","https://openalex.org/W2086465792","https://openalex.org/W2092122022","https://openalex.org/W2123101350","https://openalex.org/W2129461335","https://openalex.org/W2170506330","https://openalex.org/W2217701558","https://openalex.org/W3038420293","https://openalex.org/W3211330693","https://openalex.org/W4206033904","https://openalex.org/W6633290986","https://openalex.org/W6636113375"],"related_works":["https://openalex.org/W3208095355","https://openalex.org/W2177370417","https://openalex.org/W2052507016","https://openalex.org/W2180461068","https://openalex.org/W2051816080","https://openalex.org/W1768769760","https://openalex.org/W2413360119","https://openalex.org/W2157123855","https://openalex.org/W2984005617","https://openalex.org/W1990140521"],"abstract_inverted_index":{"We":[0,72,138,153,171],"address":[1],"the":[2,5,52,77,82,93,96,105,109,118,129,135,145,175],"problem":[3],"of":[4,7,24,54,81,84,95,120,148],"segmentation":[6,97,147],"cerebral":[8],"white":[9],"matter":[10],"structures":[11],"from":[12,21],"diffusion":[13,25,150,158],"tensor":[14,130,151],"images":[15,27,31],"(DTI).":[16],"DTI":[17],"can":[18],"be":[19,69],"estimated":[20],"a":[22,38,55,63,125,140,149],"set":[23],"weighted":[26],"and":[28,58,166,173,180],"provides":[29],"tensor-valued":[30],"where":[32],"each":[33],"voxel":[34],"is":[35,62,89,114],"assigned":[36],"with":[37,99],"3":[39,41],"times":[40],"symmetric,":[42],"positive-definite":[43],"matrix.":[44],"As":[45],"we":[46],"will":[47],"show":[48,154],"in":[49],"this":[50,121],"paper,":[51],"definition":[53],"dissimilarity":[56,101],"measure":[57],"statistics":[59,131,160],"between":[60],"tensors":[61,159],"non":[64],"trivial":[65],"task":[66],"which":[67],"must":[68],"carefully":[70],"tackled.":[71],"claim":[73],"that,":[74],"by":[75],"using":[76],"differential":[78],"geometrical":[79],"properties":[80],"manifold":[83],"multivariate":[85],"normal":[86],"distributions,":[87],"it":[88],"possible":[90],"to":[91,115,143,156],"improve":[92],"quality":[94],"obtained":[98,177],"other":[100],"measures":[102],"such":[103],"as":[104],"Euclidean":[106],"distance":[107],"or":[108],"Kullback-Leibler":[110],"divergence.":[111],"Our":[112],"goal":[113],"prove":[116],"that":[117],"choice":[119],"probability":[122,164],"metric":[123],"has":[124],"deep":[126],"impact":[127],"on":[128,134,178],"and,":[132],"hence,":[133],"achieved":[136],"results.":[137],"introduce":[139],"variational":[141],"formulation":[142],"estimate":[144,157],"optimal":[146],"image.":[152],"how":[155],"for":[161],"three":[162],"different":[163],"metrics":[165],"evaluate":[167],"their":[168],"respective":[169],"performances.":[170],"validate":[172],"compare":[174],"results":[176],"synthetic":[179],"real":[181],"datasets":[182]},"counts_by_year":[{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}