{"id":"https://openalex.org/W2140732619","doi":"https://doi.org/10.1109/isspa.2007.4555454","title":"A new proposal for 3D fiber tracking in synthetic diffusion tensor magnetic resonance images","display_name":"A new proposal for 3D fiber tracking in synthetic diffusion tensor magnetic resonance images","publication_year":2007,"publication_date":"2007-02-01","ids":{"openalex":"https://openalex.org/W2140732619","doi":"https://doi.org/10.1109/isspa.2007.4555454","mag":"2140732619"},"language":"en","primary_location":{"id":"doi:10.1109/isspa.2007.4555454","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isspa.2007.4555454","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 9th International Symposium on Signal Processing and Its Applications","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/A5054395251","display_name":"Luis M. San\u2010Jos\u00e9\u2010Revuelta","orcid":"https://orcid.org/0000-0002-8760-9577"},"institutions":[{"id":"https://openalex.org/I108103353","display_name":"Universidad de Valladolid","ror":"https://ror.org/01fvbaw18","country_code":"ES","type":"education","lineage":["https://openalex.org/I108103353"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"L. M. San-Jose-Revuelta","raw_affiliation_strings":["Department Teoriadela Senal y Comunicaciones e I.T, University of Valladolid, Spain","Dept. Teor. de la Serial y Comun. e I.T., Valladolid Univ., Valladolid"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department Teoriadela Senal y Comunicaciones e I.T, University of Valladolid, Spain","institution_ids":["https://openalex.org/I108103353"]},{"raw_affiliation_string":"Dept. Teor. de la Serial y Comun. e I.T., Valladolid Univ., Valladolid","institution_ids":["https://openalex.org/I108103353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017510847","display_name":"Marcos Mart\u00edn\u2010Fern\u00e1ndez","orcid":"https://orcid.org/0000-0001-9342-9989"},"institutions":[{"id":"https://openalex.org/I108103353","display_name":"Universidad de Valladolid","ror":"https://ror.org/01fvbaw18","country_code":"ES","type":"education","lineage":["https://openalex.org/I108103353"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"M. Martin-Fernandez","raw_affiliation_strings":["Department Teoriadela Senal y Comunicaciones e I.T, University of Valladolid, Spain","Dept. Teor. de la Serial y Comun. e I.T., Valladolid Univ., Valladolid"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department Teoriadela Senal y Comunicaciones e I.T, University of Valladolid, Spain","institution_ids":["https://openalex.org/I108103353"]},{"raw_affiliation_string":"Dept. Teor. de la Serial y Comun. e I.T., Valladolid Univ., Valladolid","institution_ids":["https://openalex.org/I108103353"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028623087","display_name":"Carlos Alberola\u2010L\u00f3pez","orcid":"https://orcid.org/0000-0003-3684-0055"},"institutions":[{"id":"https://openalex.org/I108103353","display_name":"Universidad de Valladolid","ror":"https://ror.org/01fvbaw18","country_code":"ES","type":"education","lineage":["https://openalex.org/I108103353"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"C. Alberola-Lopez","raw_affiliation_strings":["Department Teoriadela Senal y Comunicaciones e I.T, University of Valladolid, Spain","Dept. Teor. de la Serial y Comun. e I.T., Valladolid Univ., Valladolid"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department Teoriadela Senal y Comunicaciones e I.T, University of Valladolid, Spain","institution_ids":["https://openalex.org/I108103353"]},{"raw_affiliation_string":"Dept. Teor. de la Serial y Comun. e I.T., Valladolid Univ., Valladolid","institution_ids":["https://openalex.org/I108103353"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I108103353"],"apc_list":null,"apc_paid":null,"fwci":4.2373,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.94794999,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"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/T12303","display_name":"Tensor decomposition and applications","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"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/T12552","display_name":"Fetal and Pediatric Neurological Disorders","score":0.9871000051498413,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.709911584854126},{"id":"https://openalex.org/keywords/diffusion-mri","display_name":"Diffusion MRI","score":0.7043688893318176},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.6306357979774475},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6150697469711304},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5995671153068542},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.5162046551704407},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.461515873670578},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4438716173171997},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.43916308879852295},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4081553518772125},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16730448603630066}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.709911584854126},{"id":"https://openalex.org/C149550507","wikidata":"https://www.wikidata.org/wiki/Q899360","display_name":"Diffusion MRI","level":3,"score":0.7043688893318176},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.6306357979774475},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6150697469711304},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5995671153068542},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.5162046551704407},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.461515873670578},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4438716173171997},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.43916308879852295},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4081553518772125},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16730448603630066},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isspa.2007.4555454","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isspa.2007.4555454","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 9th International Symposium on Signal Processing and Its Applications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Partnerships for the goals","score":0.41999998688697815,"id":"https://metadata.un.org/sdg/17"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1991154974","https://openalex.org/W2036785860","https://openalex.org/W2074888367","https://openalex.org/W2111876604","https://openalex.org/W2131456310"],"related_works":["https://openalex.org/W2084086966","https://openalex.org/W2770593030","https://openalex.org/W1768769760","https://openalex.org/W2413360119","https://openalex.org/W2943623134","https://openalex.org/W1576270090","https://openalex.org/W2494523064","https://openalex.org/W2131307089","https://openalex.org/W3154990682","https://openalex.org/W2356293051"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"a":[3,49],"new":[4,61],"fiber":[5],"tracking":[6,26],"algorithm":[7,52],"to":[8,38],"be":[9],"used":[10],"with":[11,68],"diffusion":[12],"tensor":[13],"fields":[14],"acquired":[15],"via":[16],"magnetic":[17],"resonance":[18],"imaging":[19],"is":[20,45],"developed.":[21],"The":[22,42,60],"research":[23],"effort":[24],"in":[25,31,66],"fibers":[27],"of":[28,87],"nervous":[29],"cells":[30],"the":[32,39,85,93],"human":[33],"brain":[34],"affords":[35],"many":[36],"benefits":[37],"medical":[40],"community.":[41],"proposed":[43],"method":[44],"an":[46,89],"improvement":[47],"over":[48],"previously":[50],"developed":[51],"that":[53],"uses":[54],"both":[55],"geometrical":[56],"and":[57,70,76],"probabilistic":[58],"criteria.":[59],"scheme":[62],"offers":[63,84],"better":[64,74],"results":[65],"regions":[67],"branching":[69],"crossing":[71],"fibers,":[72],"showing":[73],"computational":[75],"robustness":[77],"properties.":[78],"Like":[79],"its":[80],"predecessor,":[81],"it":[82],"also":[83],"capability":[86],"reporting":[88],"uncertainty":[90],"value":[91],"for":[92],"computed":[94],"tracts.":[95]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
