{"id":"https://openalex.org/W3037451087","doi":"https://doi.org/10.1109/hpec43674.2020.9286192","title":"Accelerating MRI Reconstruction on TPUs","display_name":"Accelerating MRI Reconstruction on TPUs","publication_year":2020,"publication_date":"2020-09-22","ids":{"openalex":"https://openalex.org/W3037451087","doi":"https://doi.org/10.1109/hpec43674.2020.9286192","mag":"3037451087"},"language":"en","primary_location":{"id":"doi:10.1109/hpec43674.2020.9286192","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpec43674.2020.9286192","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE High Performance Extreme Computing Conference (HPEC)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2006.14080","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062139423","display_name":"Tianjian Lu","orcid":"https://orcid.org/0000-0002-5637-1391"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tianjian Lu","raw_affiliation_strings":["Google Research","Google Research,"],"affiliations":[{"raw_affiliation_string":"Google Research","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"Google Research,","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069758006","display_name":"Thibault Marin","orcid":"https://orcid.org/0000-0002-8669-1003"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thibault Marin","raw_affiliation_strings":["Google Research","Google Research,"],"affiliations":[{"raw_affiliation_string":"Google Research","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"Google Research,","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100690532","display_name":"Yue Zhuo","orcid":"https://orcid.org/0000-0002-5739-1896"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yue Zhuo","raw_affiliation_strings":["Google Research","Google Research,"],"affiliations":[{"raw_affiliation_string":"Google Research","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"Google Research,","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100405124","display_name":"Yifan Chen","orcid":"https://orcid.org/0000-0001-7645-623X"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yi-Fan Chen","raw_affiliation_strings":["Google Research","Google Research,"],"affiliations":[{"raw_affiliation_string":"Google Research","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"Google Research,","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062325991","display_name":"Chao Ma","orcid":"https://orcid.org/0000-0002-2016-8084"},"institutions":[{"id":"https://openalex.org/I4210087915","display_name":"Massachusetts General Hospital","ror":"https://ror.org/002pd6e78","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210087915","https://openalex.org/I48633490"]},{"id":"https://openalex.org/I4210087356","display_name":"Gordon Center for Medical Imaging","ror":"https://ror.org/004y4rj95","country_code":"US","type":"facility","lineage":["https://openalex.org/I136199984","https://openalex.org/I4210087356","https://openalex.org/I4210087915","https://openalex.org/I48633490"]},{"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":"Chao Ma","raw_affiliation_strings":["Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School"],"affiliations":[{"raw_affiliation_string":"Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School","institution_ids":["https://openalex.org/I4210087356","https://openalex.org/I136199984","https://openalex.org/I4210087915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5062139423"],"corresponding_institution_ids":["https://openalex.org/I1291425158"],"apc_list":null,"apc_paid":null,"fwci":0.897,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.69430317,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9994999766349792,"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/T11809","display_name":"Advanced NMR Techniques and Applications","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/1607","display_name":"Spectroscopy"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7123175859451294},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.6621825098991394},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5174713730812073},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.4911818206310272},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.48454537987709045},{"id":"https://openalex.org/keywords/hypercomplex-number","display_name":"Hypercomplex number","score":0.4330872893333435},{"id":"https://openalex.org/keywords/computational-science","display_name":"Computational science","score":0.4157223403453827},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3552301526069641},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.34424513578414917},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.33093032240867615},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2999759912490845},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1922810673713684}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7123175859451294},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.6621825098991394},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5174713730812073},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.4911818206310272},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48454537987709045},{"id":"https://openalex.org/C203249530","wikidata":"https://www.wikidata.org/wiki/Q837414","display_name":"Hypercomplex number","level":3,"score":0.4330872893333435},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.4157223403453827},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3552301526069641},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.34424513578414917},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.33093032240867615},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2999759912490845},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1922810673713684},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C200127275","wikidata":"https://www.wikidata.org/wiki/Q173853","display_name":"Quaternion","level":2,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/hpec43674.2020.9286192","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpec43674.2020.9286192","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE High Performance Extreme Computing Conference (HPEC)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2006.14080","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2006.14080","pdf_url":"https://arxiv.org/pdf/2006.14080","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:3037451087","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2006.14080","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2006.14080","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2006.14080","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2006.14080","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2006.14080","pdf_url":"https://arxiv.org/pdf/2006.14080","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3037451087.pdf","grobid_xml":"https://content.openalex.org/works/W3037451087.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W1509254020","https://openalex.org/W1964397874","https://openalex.org/W1993917215","https://openalex.org/W2016641965","https://openalex.org/W2036343507","https://openalex.org/W2055844022","https://openalex.org/W2080236984","https://openalex.org/W2099944953","https://openalex.org/W2101507236","https://openalex.org/W2101675075","https://openalex.org/W2115723093","https://openalex.org/W2117406892","https://openalex.org/W2124021916","https://openalex.org/W2129638195","https://openalex.org/W2142808775","https://openalex.org/W2145096794","https://openalex.org/W2150903265","https://openalex.org/W2157931750","https://openalex.org/W2164278908","https://openalex.org/W2167233877","https://openalex.org/W2168887049","https://openalex.org/W2170255449","https://openalex.org/W2296616510","https://openalex.org/W2399267115","https://openalex.org/W2525778437","https://openalex.org/W2588773459","https://openalex.org/W2606722458","https://openalex.org/W2620440553","https://openalex.org/W2752792052","https://openalex.org/W2777638777","https://openalex.org/W2790485410","https://openalex.org/W2948528583","https://openalex.org/W2953212265","https://openalex.org/W2983490771","https://openalex.org/W3004740094","https://openalex.org/W4233764193","https://openalex.org/W4249760698","https://openalex.org/W4250955649","https://openalex.org/W4292363360","https://openalex.org/W6678177865","https://openalex.org/W6679153239","https://openalex.org/W6738640236"],"related_works":["https://openalex.org/W3115527251","https://openalex.org/W2507398220","https://openalex.org/W2102909376","https://openalex.org/W3019055564","https://openalex.org/W1588180435","https://openalex.org/W2033336457","https://openalex.org/W2794285323","https://openalex.org/W1988504501","https://openalex.org/W2339161400","https://openalex.org/W1992112669","https://openalex.org/W3034790722","https://openalex.org/W3087371695","https://openalex.org/W2317923507","https://openalex.org/W2740906587","https://openalex.org/W2983429272","https://openalex.org/W3200873036","https://openalex.org/W2527299897","https://openalex.org/W2126407179","https://openalex.org/W2802313126","https://openalex.org/W2817374374"],"abstract_inverted_index":{"The":[0,102,117,138,149,171,196],"advanced":[1,39],"magnetic":[2],"resonance":[3],"(MR)":[4],"image":[5,60,209],"reconstructions":[6,27],"such":[7,159],"as":[8,17,132,147],"the":[9,23,30,34,58,88,134,155,161,175,184,193,199,204],"compressed":[10],"sensing":[11],"and":[12,110,119,141,174,198],"subspace-based":[13],"imaging":[14],"are":[15,125,145,165,179,212],"considered":[16],"large-scale,":[18],"iterative,":[19],"optimization":[20],"problems.":[21,83],"Given":[22],"large":[24],"number":[25],"of":[26,37,92,129,203],"required":[28],"by":[29],"practical":[31],"clinical":[32],"usage,":[33],"computation":[35],"time":[36],"these":[38],"reconstruction":[40,103,210],"methods":[41],"is":[42,63,104,152],"often":[43],"unacceptable.":[44],"In":[45],"this":[46],"work,":[47],"we":[48,86],"propose":[49],"using":[50],"Google's":[51],"Tensor":[52],"Processing":[53],"Units":[54],"(TPUs)":[55],"to":[56,78,97,154,191],"accelerate":[57],"MR":[59],"reconstruction.":[61],"TPU":[62,169,185,206],"an":[64],"application-specific":[65],"integrated":[66],"circuit":[67],"(ASIC)":[68],"for":[69],"machine":[70],"learning":[71],"applications,":[72],"which":[73],"has":[74],"recently":[75],"been":[76],"used":[77],"solve":[79],"large-scale":[80],"scientific":[81],"computing":[82],"As":[84],"proof-of-concept,":[85],"implement":[87],"alternating":[89],"direction":[90],"method":[91,211],"multipliers":[93],"(ADMM)":[94],"in":[95,127,133,181,189],"TensorFlow":[96],"reconstruct":[98],"images":[99],"on":[100,106],"TPUs.":[101],"based":[105,208],"multi-channel,":[107],"sparsely":[108],"sampled,":[109],"radial-trajectory":[111],"k-space":[112,157],"data":[113,150,158,172],"with":[114,183],"sparsity":[115],"constraints.":[116],"forward":[118],"inverse":[120],"non-uniform":[121],"Fourier":[122,136],"transform":[123,140],"operations":[124,144,164],"formulated":[126,146],"terms":[128],"matrix":[130],"multiplications":[131],"discrete":[135],"transform.":[137],"sparsifying":[139],"its":[142],"adjoint":[143],"convolutions.":[148],"decomposition":[151,173],"applied":[153],"measured":[156],"that":[160],"aforementioned":[162],"tensor":[163],"localized":[166],"within":[167],"individual":[168],"cores.":[170],"inter-core":[176],"communication":[177,194],"strategy":[178],"designed":[180],"accordance":[182],"interconnect":[186],"network":[187],"topology":[188],"order":[190],"minimize":[192],"time.":[195],"accuracy":[197],"high":[200],"parallel":[201],"efficiency":[202],"proposed":[205],"-":[207],"demonstrated":[213],"through":[214],"numerical":[215],"examples.":[216]},"counts_by_year":[{"year":2023,"cited_by_count":3},{"year":2021,"cited_by_count":2}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}
