{"id":"https://openalex.org/W2147720374","doi":"https://doi.org/10.1186/1687-6180-2012-82","title":"Using learned under-sampling pattern for increasing speed of cardiac cine MRI based on compressive sensing principles","display_name":"Using learned under-sampling pattern for increasing speed of cardiac cine MRI based on compressive sensing principles","publication_year":2012,"publication_date":"2012-04-13","ids":{"openalex":"https://openalex.org/W2147720374","doi":"https://doi.org/10.1186/1687-6180-2012-82","mag":"2147720374"},"language":"en","primary_location":{"id":"doi:10.1186/1687-6180-2012-82","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1687-6180-2012-82","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/1687-6180-2012-82","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/1687-6180-2012-82","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007650429","display_name":"Pooria Zamani","orcid":null},"institutions":[{"id":"https://openalex.org/I23946033","display_name":"University of Tehran","ror":"https://ror.org/05vf56z40","country_code":"IR","type":"education","lineage":["https://openalex.org/I23946033"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Pooria Zamani","raw_affiliation_strings":["Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, University of Tehran, Tehran, 1439957131, Iran"],"affiliations":[{"raw_affiliation_string":"Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, University of Tehran, Tehran, 1439957131, Iran","institution_ids":["https://openalex.org/I23946033"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015281486","display_name":"Mohammad H. Kayvanrad","orcid":null},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Mohammad Kayvanrad","raw_affiliation_strings":["Imaging Research Laboratories, Robarts Research Institute, The University of Western Ontario, 100 Perth Drive, London, N6A 5K8, ON, Canada"],"affiliations":[{"raw_affiliation_string":"Imaging Research Laboratories, Robarts Research Institute, The University of Western Ontario, 100 Perth Drive, London, N6A 5K8, ON, Canada","institution_ids":["https://openalex.org/I125749732"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058761102","display_name":"Hamid Soltanian\u2010Zadeh","orcid":"https://orcid.org/0000-0002-7302-6856"},"institutions":[{"id":"https://openalex.org/I23946033","display_name":"University of Tehran","ror":"https://ror.org/05vf56z40","country_code":"IR","type":"education","lineage":["https://openalex.org/I23946033"]},{"id":"https://openalex.org/I4210146419","display_name":"Institute for Research in Fundamental Sciences","ror":"https://ror.org/04xreqs31","country_code":"IR","type":"facility","lineage":["https://openalex.org/I4210146419"]},{"id":"https://openalex.org/I185443292","display_name":"Wayne State University","ror":"https://ror.org/01070mq45","country_code":"US","type":"education","lineage":["https://openalex.org/I185443292"]},{"id":"https://openalex.org/I154057602","display_name":"Henry Ford Health System","ror":"https://ror.org/02kwnkm68","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I154057602"]}],"countries":["IR","US"],"is_corresponding":false,"raw_author_name":"Hamid Soltanian-Zadeh","raw_affiliation_strings":["Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, University of Tehran, Tehran, 1439957131, Iran","Department of Radiology, Wayne State University, Detroit, MI, 48202, USA","Radiology Image Analysis Lab, Henry Ford Health System, Detroit, MI, 48202, USA","School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, 1954856316, Iran"],"affiliations":[{"raw_affiliation_string":"Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, University of Tehran, Tehran, 1439957131, Iran","institution_ids":["https://openalex.org/I23946033"]},{"raw_affiliation_string":"Department of Radiology, Wayne State University, Detroit, MI, 48202, USA","institution_ids":["https://openalex.org/I185443292"]},{"raw_affiliation_string":"Radiology Image Analysis Lab, Henry Ford Health System, Detroit, MI, 48202, USA","institution_ids":["https://openalex.org/I154057602"]},{"raw_affiliation_string":"School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, 1954856316, Iran","institution_ids":["https://openalex.org/I4210146419"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5007650429"],"corresponding_institution_ids":["https://openalex.org/I23946033"],"apc_list":{"value":1140,"currency":"GBP","value_usd":1398},"apc_paid":{"value":1140,"currency":"GBP","value_usd":1398},"fwci":1.0493,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.78067796,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"2012","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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":1.0,"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":0.9998999834060669,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/compressed-sensing","display_name":"Compressed sensing","score":0.6292639374732971},{"id":"https://openalex.org/keywords/k-space","display_name":"k-space","score":0.6156124472618103},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6097315549850464},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5433093309402466},{"id":"https://openalex.org/keywords/cardiac-cycle","display_name":"Cardiac cycle","score":0.531532347202301},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5267878174781799},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.47395941615104675},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4650610089302063},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.44980350136756897},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4379047155380249},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4280685484409332},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.40516164898872375},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3899271488189697},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.290263831615448},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.18721887469291687}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.6292639374732971},{"id":"https://openalex.org/C197413143","wikidata":"https://www.wikidata.org/wiki/Q1050490","display_name":"k-space","level":3,"score":0.6156124472618103},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6097315549850464},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5433093309402466},{"id":"https://openalex.org/C99398487","wikidata":"https://www.wikidata.org/wiki/Q257319","display_name":"Cardiac cycle","level":2,"score":0.531532347202301},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5267878174781799},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.47395941615104675},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4650610089302063},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.44980350136756897},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4379047155380249},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4280685484409332},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.40516164898872375},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3899271488189697},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.290263831615448},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18721887469291687},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","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},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/1687-6180-2012-82","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1687-6180-2012-82","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/1687-6180-2012-82","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:digitalcommons.wayne.edu:biomedcentral-1042","is_oa":false,"landing_page_url":"https://digitalcommons.wayne.edu/biomedcentral/43","pdf_url":null,"source":{"id":"https://openalex.org/S4377196394","display_name":"DigitalCommons - WayneState (Wayne State University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I185443292","host_organization_name":"Wayne State University","host_organization_lineage":["https://openalex.org/I185443292"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Wayne State University Associated BioMed Central Scholarship","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/1687-6180-2012-82","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1687-6180-2012-82","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/1687-6180-2012-82","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3497591915","display_name":null,"funder_award_id":"(NIH)","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"}],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2147720374.pdf","grobid_xml":"https://content.openalex.org/works/W2147720374.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W242464784","https://openalex.org/W1490760466","https://openalex.org/W1521875821","https://openalex.org/W1979954835","https://openalex.org/W2005836623","https://openalex.org/W2007103423","https://openalex.org/W2056775112","https://openalex.org/W2075358160","https://openalex.org/W2082025849","https://openalex.org/W2090268707","https://openalex.org/W2097459612","https://openalex.org/W2101675075","https://openalex.org/W2103373759","https://openalex.org/W2111388536","https://openalex.org/W2115706991","https://openalex.org/W2116523778","https://openalex.org/W2123346066","https://openalex.org/W2132122471","https://openalex.org/W2145096794","https://openalex.org/W2147516887","https://openalex.org/W2155268695","https://openalex.org/W2167233877","https://openalex.org/W2168878441","https://openalex.org/W2168887049","https://openalex.org/W2296616510","https://openalex.org/W2799061466","https://openalex.org/W4205687621","https://openalex.org/W4233764193","https://openalex.org/W4239443620","https://openalex.org/W4249760698","https://openalex.org/W4250955649"],"related_works":["https://openalex.org/W2953058328","https://openalex.org/W1542224353","https://openalex.org/W1661087619","https://openalex.org/W2750730210","https://openalex.org/W2187562763","https://openalex.org/W2907262162","https://openalex.org/W2212041357","https://openalex.org/W2339684922","https://openalex.org/W2076898293","https://openalex.org/W2895530314"],"abstract_inverted_index":{"Abstract":[0],"This":[1],"article":[2],"presents":[3],"a":[4,54,71],"compressive":[5],"sensing":[6],"approach":[7,212],"for":[8,168,192,219],"reducing":[9],"data":[10,40,91,102,117,141,169],"acquisition":[11,92],"time":[12,68,84,96,107,121],"in":[13,42],"cardiac":[14,21,30,88,220],"cine":[15,22,221],"magnetic":[16],"resonance":[17],"imaging":[18],"(MRI).":[19],"In":[20,50],"MRI,":[23],"several":[24],"images":[25,183,200,204],"are":[26,63,79,123,131,166],"acquired":[27,41,64,80,103],"throughout":[28],"the":[29,38,43,51,59,66,76,82,87,94,101,105,115,119,129,134,155,172,182,185,194,199],"cycle,":[31],"each":[32],"of":[33,58,75,86,114,136,217],"which":[34],"is":[35,98,142,178],"reconstructed":[36],"from":[37,100,162,184],"raw":[39],"Fourier":[44],"transform":[45],"domain,":[46],"traditionally":[47],"called":[48],"k-space.":[49],"proposed":[52,190,210],"approach,":[53],"majority,":[55],"e.g.,":[56,73],"62.5%,":[57],"k-space":[60,77,116,187,195],"lines":[61,78],"(trajectories)":[62],"at":[65,81,93,104,118],"odd":[67,106,120],"points":[69,85,97,122],"and":[70,128,149,197],"minority,":[72],"37.5%,":[74],"even":[83,95],"cycle.":[89],"Optimal":[90],"learned":[99],"points.":[108],"To":[109],"this":[110],"end,":[111,173],"statistical":[112],"features":[113],"clustered":[124],"by":[125],"fuzzy":[126],"c-means":[127],"results":[130],"considered":[132],"as":[133],"states":[135],"Markov":[137,147],"chains.":[138],"The":[139,189,209],"resulting":[140],"used":[143,179],"to":[144,158,180,206],"train":[145],"hidden":[146],"models":[148],"find":[150],"their":[151],"transition":[152,159],"matrices.":[153],"Then,":[154],"trajectories":[156,196],"corresponding":[157],"matrices":[160],"far":[161],"an":[163,174,214],"identity":[164],"matrix":[165],"selected":[167],"acquisition.":[170],"At":[171],"iterative":[175],"thresholding":[176],"algorithm":[177],"reconstruct":[181],"under-sampled":[186],"datasets.":[188],"approaches":[191],"selecting":[193],"reconstructing":[198],"generate":[201],"more":[202],"accurate":[203],"compared":[205],"alternative":[207],"methods.":[208],"under-sampling":[211],"achieves":[213],"acceleration":[215],"factor":[216],"2":[218],"MRI.":[222]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
