{"id":"https://openalex.org/W3137726214","doi":null,"title":"Generative SToRM: A novel approach for joint alignment and recovery of multi-slice dynamic MRI.","display_name":"Generative SToRM: A novel approach for joint alignment and recovery of multi-slice dynamic MRI.","publication_year":2021,"publication_date":"2021-01-20","ids":{"openalex":"https://openalex.org/W3137726214","mag":"3137726214"},"language":"en","primary_location":{"id":"mag:3137726214","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2101.08196","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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},"volume":null,"type":"preprint","indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://export.arxiv.org/pdf/2101.08196","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059507084","display_name":"Qing Zou","orcid":"https://orcid.org/0000-0002-2729-2491","observed_orcids":["https://orcid.org/0000-0002-2729-2491"]},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qing Zou","raw_affiliation_strings":["University of Iowa"],"raw_orcid":"https://orcid.org/0000-0002-2729-2491","affiliations":[{"raw_affiliation_string":"University of Iowa","institution_ids":["https://openalex.org/I126307644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048576838","display_name":"Abdul Haseeb Ahmed","orcid":"https://orcid.org/0000-0002-7037-9621","observed_orcids":["https://orcid.org/0000-0002-7037-9621"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Abdul Haseeb Ahmed","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-7037-9621","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023586623","display_name":"Prashant Nagpal","orcid":"https://orcid.org/0000-0003-2347-034X","observed_orcids":["https://orcid.org/0000-0003-2347-034X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Prashant Nagpal","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036149073","display_name":"Sarv Priya","orcid":"https://orcid.org/0000-0003-2442-1902","observed_orcids":["https://orcid.org/0000-0003-2442-1902"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sarv Priya","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-2442-1902","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013301536","display_name":"Rolf F. Schulte","orcid":"https://orcid.org/0000-0002-1334-1264","observed_orcids":["https://orcid.org/0000-0002-1334-1264","https://orcid.org/0000-0002-7892-2756"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rolf F. Schulte","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-1334-1264","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5072299998","display_name":"Mathews Jacob","orcid":"https://orcid.org/0000-0001-6196-3933","observed_orcids":["https://orcid.org/0000-0001-6196-3933"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mathews Jacob","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-6196-3933","affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9916999936103821,"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/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9916999936103821,"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/T10372","display_name":"Cardiac Imaging and Diagnostics","score":0.0010000000474974513,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.0005000000237487257,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cardiac-mri","display_name":"cardiac MRI","score":0.6830000281333923},{"id":"https://openalex.org/keywords/free-breathing-mri","display_name":"free-breathing MRI","score":0.7850000262260437},{"id":"https://openalex.org/keywords/multi-slice-mri","display_name":"multi-slice MRI","score":0.7080000042915344},{"id":"https://openalex.org/keywords/image-reconstruction","display_name":"image reconstruction","score":0.6380000114440918},{"id":"https://openalex.org/keywords/deep-generative-models","display_name":"deep generative models","score":0.6140000224113464},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"unsupervised learning","score":0.8579999804496765}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7313281297683716},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5338160991668701},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5133654475212097},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.4978830814361572},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47238922119140625},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.46469590067863464},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.46399351954460144},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45905056595802307},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4512629806995392},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.42342984676361084},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3613436222076416},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.31711331009864807},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.1272459626197815},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:3137726214","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2101.08196","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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}],"best_oa_location":{"id":"mag:3137726214","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2101.08196","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1847612160","https://openalex.org/W1989549063","https://openalex.org/W2211925052","https://openalex.org/W2318839711","https://openalex.org/W2510528041","https://openalex.org/W2568900599","https://openalex.org/W2726168645","https://openalex.org/W2797196654","https://openalex.org/W2806717405","https://openalex.org/W2912009603","https://openalex.org/W2962734274","https://openalex.org/W2964013315","https://openalex.org/W2964121744","https://openalex.org/W2967522980","https://openalex.org/W2977723824","https://openalex.org/W3007743770","https://openalex.org/W3015128089","https://openalex.org/W3039473929","https://openalex.org/W3048384642","https://openalex.org/W3092507194","https://openalex.org/W3103847576"],"related_works":["https://openalex.org/W3122409077","https://openalex.org/W4401571886","https://openalex.org/W4226324173","https://openalex.org/W4385544149","https://openalex.org/W3165244505","https://openalex.org/W4308900559","https://openalex.org/W4401574740","https://openalex.org/W4319985938","https://openalex.org/W2922528425","https://openalex.org/W2986222199"],"abstract_inverted_index":{"We":[0,97],"introduce":[1],"a":[2,38],"novel":[3],"unsupervised":[4,181],"deep":[5,39],"generative":[6],"manifold":[7,129],"model":[8],"for":[9,134,188],"the":[10,27,35,53,59,67,71,77,81,86,92,100,104,108,114,117,124,131,138,145,150,159,162,165,169,174,180,186],"recovery":[11],"of":[12,37,126,144],"multi-slice":[13,28,154],"free-breathing":[14],"and":[15,55,70,116,130,156,178],"ungated":[16],"cardiac":[17,54],"MRI":[18],"from":[19,84,103,173],"highly":[20,87],"undersampled":[21,88,105],"measurements.":[22],"The":[23,63,141],"proposed":[24,68,78,146],"scheme":[25,79,147],"represents":[26],"volume":[29],"at":[30,58],"each":[31,135],"time":[32,61],"point":[33],"as":[34],"output":[36],"convolutional":[40],"neural":[41],"network":[42,82,115],"(CNN)":[43],"generator,":[44],"which":[45],"is":[46,75],"driven":[47],"by":[48],"latent":[49,101,118,132],"vectors":[50],"that":[51,76,184],"capture":[52],"respiratory":[56],"phase":[57],"specific":[60],"point.":[62],"main":[64,142],"difference":[65],"between":[66,161],"method":[69],"traditional":[72],"CNN":[73],"approaches":[74],"learns":[80],"parameters":[83],"only":[85],"data":[89,106,155],"rather":[90],"than":[91],"extensive":[93,189],"fully-sampled":[94],"training":[95,190],"data.":[96,191],"also":[98],"learn":[99],"codes":[102,119,133],"using":[107],"stochastic":[109],"gradient":[110],"descent.":[111],"Regularizations":[112],"on":[113,158],"are":[120,148],"introduced":[121],"to":[122,152,167],"encourage":[123],"learning":[125,182],"smooth":[127],"image":[128],"slice":[136],"have":[137],"same":[139],"distribution.":[140],"benefits":[143],"(a)":[149],"ability":[151,166],"align":[153],"capitalize":[157],"redundancy":[160],"slices;":[163],"(b)":[164],"estimate":[168],"gating":[170],"information":[171],"directly":[172],"k-t":[175],"space":[176],"data;":[177],"(c)":[179],"strategy":[183],"eliminates":[185],"need":[187]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2021-03-29T00:00:00"}