{"id":"https://openalex.org/W2989263382","doi":"https://doi.org/10.1109/icassp40776.2020.9053297","title":"Joint Optimization of Sampling Patterns and Deep Priors for Improved Parallel MRI","display_name":"Joint Optimization of Sampling Patterns and Deep Priors for Improved Parallel MRI","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W2989263382","doi":"https://doi.org/10.1109/icassp40776.2020.9053297","mag":"2989263382"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9053297","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053297","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1911.02945","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076929884","display_name":"Hemant Kumar Aggarwal","orcid":"https://orcid.org/0000-0002-3756-9765"},"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":true,"raw_author_name":"Hemant K. Aggarwal","raw_affiliation_strings":["University of Iowa, Iowa, USA","University of Iowa Iowa USA"],"affiliations":[{"raw_affiliation_string":"University of Iowa, Iowa, USA","institution_ids":["https://openalex.org/I126307644"]},{"raw_affiliation_string":"University of Iowa Iowa USA","institution_ids":["https://openalex.org/I126307644"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072299998","display_name":"Mathews Jacob","orcid":"https://orcid.org/0000-0001-6196-3933"},"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":"Mathews Jacob","raw_affiliation_strings":["University of Iowa, Iowa, USA","University of Iowa Iowa USA"],"affiliations":[{"raw_affiliation_string":"University of Iowa, Iowa, USA","institution_ids":["https://openalex.org/I126307644"]},{"raw_affiliation_string":"University of Iowa Iowa USA","institution_ids":["https://openalex.org/I126307644"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5076929884"],"corresponding_institution_ids":["https://openalex.org/I126307644"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.00286431,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"13","issue":null,"first_page":"8901","last_page":"8905"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9995999932289124,"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":0.9995999932289124,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9983999729156494,"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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7343888282775879},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.7134317755699158},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.6639413237571716},{"id":"https://openalex.org/keywords/decoupling","display_name":"Decoupling (probability)","score":0.6283887028694153},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.6018607020378113},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.5505601763725281},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5431635975837708},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.5114173293113708},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4676833748817444},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4618145227432251},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.4412951171398163},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42286789417266846},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.40657711029052734},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3651208281517029},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3566247820854187},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35265493392944336},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3289657235145569},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12512758374214172},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.1073753833770752},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09126338362693787}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7343888282775879},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.7134317755699158},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.6639413237571716},{"id":"https://openalex.org/C205606062","wikidata":"https://www.wikidata.org/wiki/Q5249645","display_name":"Decoupling (probability)","level":2,"score":0.6283887028694153},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.6018607020378113},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.5505601763725281},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5431635975837708},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.5114173293113708},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4676833748817444},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4618145227432251},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.4412951171398163},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42286789417266846},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.40657711029052734},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3651208281517029},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3566247820854187},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35265493392944336},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3289657235145569},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12512758374214172},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.1073753833770752},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09126338362693787},{"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/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","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":3,"locations":[{"id":"doi:10.1109/icassp40776.2020.9053297","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053297","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"mag:2989263382","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1911.02945","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:10.17023/6frk-k817","is_oa":true,"landing_page_url":"https://doi.org/10.17023/6frk-k817","pdf_url":null,"source":{"id":"https://openalex.org/S7407051697","display_name":"IEEE RESOURCE CENTERS","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"mag:2989263382","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1911.02945","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},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2117649283","https://openalex.org/W2130102503","https://openalex.org/W2584483805","https://openalex.org/W2604388535","https://openalex.org/W2751646824","https://openalex.org/W2773850766","https://openalex.org/W2798774029","https://openalex.org/W2963439178","https://openalex.org/W2964120646","https://openalex.org/W4233764193","https://openalex.org/W6686055759","https://openalex.org/W6751413701","https://openalex.org/W6764294173"],"related_works":["https://openalex.org/W3015334565","https://openalex.org/W2995396522","https://openalex.org/W3111988465","https://openalex.org/W2945831440","https://openalex.org/W2887505908","https://openalex.org/W2884293458","https://openalex.org/W2912580417","https://openalex.org/W3094286386","https://openalex.org/W3133750041","https://openalex.org/W2033514934","https://openalex.org/W3046934520","https://openalex.org/W3134661769","https://openalex.org/W2982598275","https://openalex.org/W2908176780","https://openalex.org/W2956625312","https://openalex.org/W3160813006","https://openalex.org/W3026891690","https://openalex.org/W2914014776","https://openalex.org/W3002533530"],"abstract_inverted_index":{"Multichannel":[0],"imaging":[1],"techniques":[2],"are":[3,31],"widely":[4],"used":[5],"in":[6,81],"MRI":[7],"to":[8,37,70,103],"reduce":[9],"the":[10,50,56,59,63,73,77,90,94,99,115,122],"scan":[11],"time.":[12],"These":[13],"schemes":[14],"typically":[15],"perform":[16],"undersampled":[17],"acquisition":[18],"and":[19,76,106],"utilize":[20],"compressed-sensing":[21],"based":[22],"regularized":[23],"reconstruction":[24,78],"algorithms.":[25],"Model-based":[26],"deep":[27],"learning":[28],"(MoDL)":[29],"frameworks":[30],"now":[32],"emerging":[33],"as":[34],"powerful":[35],"alternatives":[36],"compressed":[38],"sensing,":[39],"with":[40],"significantly":[41,120],"improved":[42,87,104,108],"image":[43,60,123],"quality.":[44,124],"In":[45],"this":[46],"work,":[47],"we":[48],"investigate":[49],"impact":[51],"of":[52,58,89],"sampling":[53,74,95],"patterns":[54,96],"on":[55],"quality":[57],"recovered":[61],"using":[62],"MoDL":[64,82,100],"algorithm.":[65],"We":[66],"introduce":[67],"a":[68],"scheme":[69,101],"jointly":[71],"optimize":[72],"pattern":[75],"network":[79,91],"parameters":[80,92],"for":[83],"parallel":[84],"MRI.":[85],"The":[86],"decoupling":[88],"from":[93],"offered":[97],"by":[98],"translates":[102],"optimization":[105],"thus":[107],"performance.":[109],"Preliminary":[110],"experimental":[111],"results":[112],"demonstrate":[113],"that":[114],"proposed":[116],"joint":[117],"opti-mization":[118],"framework":[119],"improves":[121]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}