{"id":"https://openalex.org/W1975800953","doi":"https://doi.org/10.1109/asap.2013.6567587","title":"Accelerating nonlinear diffusion tensor estimation for medical image processing using high performance GPU clusters","display_name":"Accelerating nonlinear diffusion tensor estimation for medical image processing using high performance GPU clusters","publication_year":2013,"publication_date":"2013-06-01","ids":{"openalex":"https://openalex.org/W1975800953","doi":"https://doi.org/10.1109/asap.2013.6567587","mag":"1975800953"},"language":"en","primary_location":{"id":"doi:10.1109/asap.2013.6567587","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asap.2013.6567587","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE 24th International Conference on Application-Specific Systems, Architectures and Processors","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/A5103071282","display_name":"Vinh Dang","orcid":"https://orcid.org/0000-0002-4958-6159"},"institutions":[{"id":"https://openalex.org/I168959743","display_name":"University of America","ror":"https://ror.org/03s0c9350","country_code":"US","type":"education","lineage":["https://openalex.org/I168959743"]},{"id":"https://openalex.org/I84470341","display_name":"Catholic University of America","ror":"https://ror.org/047yk3s18","country_code":"US","type":"education","lineage":["https://openalex.org/I84470341"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Vinh Q. Dang","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Catholic University of America, Washington, DC, DC, USA","Dept. of Electr. Eng. & Comput. Sci., Catholic Univ. of America, Washington, DC, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Catholic University of America, Washington, DC, DC, USA","institution_ids":["https://openalex.org/I168959743","https://openalex.org/I84470341"]},{"raw_affiliation_string":"Dept. of Electr. Eng. & Comput. Sci., Catholic Univ. of America, Washington, DC, USA","institution_ids":["https://openalex.org/I84470341"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057201097","display_name":"Esam El\u2010Araby","orcid":"https://orcid.org/0000-0002-4575-1049"},"institutions":[{"id":"https://openalex.org/I84470341","display_name":"Catholic University of America","ror":"https://ror.org/047yk3s18","country_code":"US","type":"education","lineage":["https://openalex.org/I84470341"]},{"id":"https://openalex.org/I168959743","display_name":"University of America","ror":"https://ror.org/03s0c9350","country_code":"US","type":"education","lineage":["https://openalex.org/I168959743"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Esam El-Araby","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Catholic University of America, Washington, DC, DC, USA","Dept. of Electr. Eng. & Comput. Sci., Catholic Univ. of America, Washington, DC, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Catholic University of America, Washington, DC, DC, USA","institution_ids":["https://openalex.org/I168959743","https://openalex.org/I84470341"]},{"raw_affiliation_string":"Dept. of Electr. Eng. & Comput. Sci., Catholic Univ. of America, Washington, DC, USA","institution_ids":["https://openalex.org/I84470341"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056671659","display_name":"Lam Dao","orcid":null},"institutions":[{"id":"https://openalex.org/I84470341","display_name":"Catholic University of America","ror":"https://ror.org/047yk3s18","country_code":"US","type":"education","lineage":["https://openalex.org/I84470341"]},{"id":"https://openalex.org/I168959743","display_name":"University of America","ror":"https://ror.org/03s0c9350","country_code":"US","type":"education","lineage":["https://openalex.org/I168959743"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lam H. Dao","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Catholic University of America, Washington, DC, DC, USA","Dept. of Electr. Eng. & Comput. Sci., Catholic Univ. of America, Washington, DC, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Catholic University of America, Washington, DC, DC, USA","institution_ids":["https://openalex.org/I168959743","https://openalex.org/I84470341"]},{"raw_affiliation_string":"Dept. of Electr. Eng. & Comput. Sci., Catholic Univ. of America, Washington, DC, USA","institution_ids":["https://openalex.org/I84470341"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059247040","display_name":"Lin\u2010Ching Chang","orcid":"https://orcid.org/0000-0002-7780-5742"},"institutions":[{"id":"https://openalex.org/I84470341","display_name":"Catholic University of America","ror":"https://ror.org/047yk3s18","country_code":"US","type":"education","lineage":["https://openalex.org/I84470341"]},{"id":"https://openalex.org/I168959743","display_name":"University of America","ror":"https://ror.org/03s0c9350","country_code":"US","type":"education","lineage":["https://openalex.org/I168959743"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lin-Ching Chang","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Catholic University of America, Washington, DC, DC, USA","Dept. of Electr. Eng. & Comput. Sci., Catholic Univ. of America, Washington, DC, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Catholic University of America, Washington, DC, DC, USA","institution_ids":["https://openalex.org/I168959743","https://openalex.org/I84470341"]},{"raw_affiliation_string":"Dept. of Electr. Eng. & Comput. Sci., Catholic Univ. of America, Washington, DC, USA","institution_ids":["https://openalex.org/I84470341"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103071282"],"corresponding_institution_ids":["https://openalex.org/I168959743","https://openalex.org/I84470341"],"apc_list":null,"apc_paid":null,"fwci":0.2581,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.61249555,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"201","issue":null,"first_page":"265","last_page":"268"},"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":0.996399998664856,"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":0.9623000025749207,"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/diffusion-mri","display_name":"Diffusion MRI","score":0.840038537979126},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.7539563179016113},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7386770248413086},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.577860414981842},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.5447240471839905},{"id":"https://openalex.org/keywords/univariate","display_name":"Univariate","score":0.4853190779685974},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47828444838523865},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.45218557119369507},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4438026249408722},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40388965606689453},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36187684535980225},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35161757469177246},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.3465486764907837},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.3146955966949463},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19968584179878235},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.17563414573669434},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.15160977840423584},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10513868927955627},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.08379516005516052}],"concepts":[{"id":"https://openalex.org/C149550507","wikidata":"https://www.wikidata.org/wiki/Q899360","display_name":"Diffusion MRI","level":3,"score":0.840038537979126},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.7539563179016113},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7386770248413086},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.577860414981842},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.5447240471839905},{"id":"https://openalex.org/C199163554","wikidata":"https://www.wikidata.org/wiki/Q1681619","display_name":"Univariate","level":3,"score":0.4853190779685974},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47828444838523865},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.45218557119369507},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4438026249408722},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40388965606689453},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36187684535980225},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35161757469177246},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.3465486764907837},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.3146955966949463},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19968584179878235},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.17563414573669434},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.15160977840423584},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10513868927955627},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.08379516005516052},{"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/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/asap.2013.6567587","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asap.2013.6567587","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE 24th International Conference on Application-Specific Systems, Architectures and Processors","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W72987253","https://openalex.org/W1543577391","https://openalex.org/W1575841671","https://openalex.org/W2020049909","https://openalex.org/W2022530159","https://openalex.org/W2031317662","https://openalex.org/W2086660842","https://openalex.org/W2087070363","https://openalex.org/W2108266785","https://openalex.org/W2110431535","https://openalex.org/W2124866764","https://openalex.org/W2136645720","https://openalex.org/W2139158372","https://openalex.org/W2158402095","https://openalex.org/W2170323558","https://openalex.org/W2256578114","https://openalex.org/W2407604849","https://openalex.org/W4256536686","https://openalex.org/W6632683294"],"related_works":["https://openalex.org/W1828158523","https://openalex.org/W2049578243","https://openalex.org/W2122079181","https://openalex.org/W2000145235","https://openalex.org/W1985848810","https://openalex.org/W2889939530","https://openalex.org/W2399195672","https://openalex.org/W3121881699","https://openalex.org/W2748838164","https://openalex.org/W2066015000"],"abstract_inverted_index":{"Diffusion":[0,44],"Tensor":[1],"Imaging":[2],"(DTI)":[3],"is":[4,74],"a":[5,51,64],"non-invasive":[6],"magnetic":[7],"resonance":[8],"technique":[9],"that":[10],"produces":[11],"in":[12,38,99,113,123,126],"vivo":[13],"images":[14,62],"of":[15,41,59,66,86,93,143,153,167],"biological":[16],"tissues":[17],"with":[18],"local":[19],"microstructural":[20],"characteristics":[21],"such":[22],"as":[23,63],"water":[24],"diffusion.":[25],"It":[26],"can":[27,78,137,146],"be":[28,79,147],"used,":[29],"for":[30],"example,":[31],"to":[32,128,149,164],"localize":[33],"white":[34],"matter":[35],"lesions,":[36],"or":[37,161],"neuro-navigation":[39],"surgery":[40],"brain":[42,116],"tumors.":[43],"tensor":[45,101,124],"maps":[46],"are":[47,111,159],"usually":[48],"computed":[49],"on":[50],"voxel-by-voxel":[52],"basis":[53],"by":[54,103],"fitting":[55,125],"the":[56,83,91,105,140],"signal":[57],"intensities":[58],"diffusion":[60,100],"weighted":[61],"function":[65],"their":[67],"corresponding":[68],"data":[69],"acquisition":[70],"parameters.":[71],"This":[72,88],"processing":[73],"highly":[75],"computation-intensive":[76],"and":[77,118,145],"time-consuming":[80],"which":[81],"constraints":[82],"clinical":[84,141],"use":[85,142],"DTI.":[87],"study":[89],"presents":[90],"application":[92],"using":[94,169],"high":[95],"performance":[96,121],"GPU":[97,134],"clusters":[98],"estimation":[102],"accelerating":[104],"multivariate":[106],"non-linear":[107],"regression.":[108],"The":[109,132],"results":[110],"tested":[112],"simulated":[114],"DTI":[115,154,168],"datasets":[117],"show":[119],"significant":[120],"gain":[122],"addition":[127],"favorable":[129],"scalability":[130],"characteristics.":[131],"proposed":[133],"implementation":[135],"framework":[136],"further":[138],"promote":[139],"DTI,":[144],"used":[148],"accelerate":[150],"statistical":[151],"analysis":[152],"where":[155],"Monte":[156],"Carlo":[157],"simulations":[158],"employed,":[160],"readily":[162],"applied":[163],"quantitative":[165],"assessment":[166],"bootstrap":[170],"analysis.":[171]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}