{"id":"https://openalex.org/W3172319064","doi":"https://doi.org/10.1109/ieeeconf51394.2020.9443403","title":"Image Reconstruction for MRI using Deep CNN Priors Trained without Groundtruth","display_name":"Image Reconstruction for MRI using Deep CNN Priors Trained without Groundtruth","publication_year":2020,"publication_date":"2020-11-01","ids":{"openalex":"https://openalex.org/W3172319064","doi":"https://doi.org/10.1109/ieeeconf51394.2020.9443403","mag":"3172319064"},"language":"en","primary_location":{"id":"doi:10.1109/ieeeconf51394.2020.9443403","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf51394.2020.9443403","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 54th Asilomar Conference on Signals, Systems, and Computers","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/A5028095390","display_name":"Weijie Gan","orcid":"https://orcid.org/0000-0003-3604-784X"},"institutions":[{"id":"https://openalex.org/I204465549","display_name":"Washington University in St. Louis","ror":"https://ror.org/01yc7t268","country_code":"US","type":"education","lineage":["https://openalex.org/I204465549"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Weijie Gan","raw_affiliation_strings":["Department of Computer Science and Engineering, Washington University, St. Louis, MO, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Washington University, St. Louis, MO, USA","institution_ids":["https://openalex.org/I204465549"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066831518","display_name":"Cihat Eldeniz","orcid":"https://orcid.org/0000-0002-4457-0916"},"institutions":[{"id":"https://openalex.org/I4210102181","display_name":"Mallinckrodt (United States)","ror":"https://ror.org/01akman82","country_code":"US","type":"company","lineage":["https://openalex.org/I4210102181"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cihat Eldeniz","raw_affiliation_strings":["Mallinckrodt Institute of Radiology, Washington University, St. Louis, MO, USA"],"affiliations":[{"raw_affiliation_string":"Mallinckrodt Institute of Radiology, Washington University, St. Louis, MO, USA","institution_ids":["https://openalex.org/I4210102181"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100440970","display_name":"Jiaming Liu","orcid":"https://orcid.org/0000-0002-1042-4443"},"institutions":[{"id":"https://openalex.org/I204465549","display_name":"Washington University in St. Louis","ror":"https://ror.org/01yc7t268","country_code":"US","type":"education","lineage":["https://openalex.org/I204465549"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiaming Liu","raw_affiliation_strings":["Department of Electrical and Systems Engineering, Washington University, St. Louis, MO, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Systems Engineering, Washington University, St. Louis, MO, USA","institution_ids":["https://openalex.org/I204465549"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101823158","display_name":"Sihao Chen","orcid":"https://orcid.org/0000-0001-8416-4261"},"institutions":[{"id":"https://openalex.org/I204465549","display_name":"Washington University in St. Louis","ror":"https://ror.org/01yc7t268","country_code":"US","type":"education","lineage":["https://openalex.org/I204465549"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sihao Chen","raw_affiliation_strings":["Department of Biomedical Engineering, Washington University, St. Louis, MO, USA"],"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, Washington University, St. Louis, MO, USA","institution_ids":["https://openalex.org/I204465549"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052040538","display_name":"Hongyu An","orcid":"https://orcid.org/0000-0001-6459-2269"},"institutions":[{"id":"https://openalex.org/I4210102181","display_name":"Mallinckrodt (United States)","ror":"https://ror.org/01akman82","country_code":"US","type":"company","lineage":["https://openalex.org/I4210102181"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongyu An","raw_affiliation_strings":["Mallinckrodt Institute of Radiology, Washington University, St. Louis, MO, USA"],"affiliations":[{"raw_affiliation_string":"Mallinckrodt Institute of Radiology, Washington University, St. Louis, MO, USA","institution_ids":["https://openalex.org/I4210102181"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024602237","display_name":"Ulugbek S. Kamilov","orcid":"https://orcid.org/0000-0001-6770-3278"},"institutions":[{"id":"https://openalex.org/I204465549","display_name":"Washington University in St. Louis","ror":"https://ror.org/01yc7t268","country_code":"US","type":"education","lineage":["https://openalex.org/I204465549"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ulugbek S. Kamilov","raw_affiliation_strings":["Department of Computer Science and Engineering, Washington University, St. Louis, MO, USA","Department of Electrical and Systems Engineering, Washington University, St. Louis, MO, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Washington University, St. Louis, MO, USA","institution_ids":["https://openalex.org/I204465549"]},{"raw_affiliation_string":"Department of Electrical and Systems Engineering, Washington University, St. Louis, MO, USA","institution_ids":["https://openalex.org/I204465549"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5028095390"],"corresponding_institution_ids":["https://openalex.org/I204465549"],"apc_list":null,"apc_paid":null,"fwci":0.4461,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.6893246,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"475","last_page":"479"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9998000264167786,"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":0.9998000264167786,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9998000264167786,"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/T11993","display_name":"Atomic and Subatomic Physics Research","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"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/prior-probability","display_name":"Prior probability","score":0.8624052405357361},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7263928055763245},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7228716015815735},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6813889741897583},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.6491210460662842},{"id":"https://openalex.org/keywords/hallucinating","display_name":"Hallucinating","score":0.6307244300842285},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6084445714950562},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.5499283671379089},{"id":"https://openalex.org/keywords/data-consistency","display_name":"Data consistency","score":0.5090124607086182},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49843597412109375},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4934214651584625},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4635566473007202},{"id":"https://openalex.org/keywords/artifact","display_name":"Artifact (error)","score":0.45266610383987427},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.44569846987724304},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.433824747800827},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.40597715973854065},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.10820698738098145}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.8624052405357361},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7263928055763245},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7228716015815735},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6813889741897583},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.6491210460662842},{"id":"https://openalex.org/C2911011789","wikidata":"https://www.wikidata.org/wiki/Q130741","display_name":"Hallucinating","level":2,"score":0.6307244300842285},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6084445714950562},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5499283671379089},{"id":"https://openalex.org/C93361087","wikidata":"https://www.wikidata.org/wiki/Q4426698","display_name":"Data consistency","level":2,"score":0.5090124607086182},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49843597412109375},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4934214651584625},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4635566473007202},{"id":"https://openalex.org/C2779010991","wikidata":"https://www.wikidata.org/wiki/Q2720909","display_name":"Artifact (error)","level":2,"score":0.45266610383987427},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.44569846987724304},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.433824747800827},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.40597715973854065},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.10820698738098145},{"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":"doi:10.1109/ieeeconf51394.2020.9443403","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf51394.2020.9443403","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 54th Asilomar Conference on Signals, Systems, and Computers","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320310181","display_name":"Institute of Clinical and Translational Sciences","ror":"https://ror.org/01yc7t268"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1906770428","https://openalex.org/W2014547837","https://openalex.org/W2056370875","https://openalex.org/W2087416986","https://openalex.org/W2101675075","https://openalex.org/W2113030459","https://openalex.org/W2156706175","https://openalex.org/W2164278908","https://openalex.org/W2573726823","https://openalex.org/W2625143103","https://openalex.org/W2784108798","https://openalex.org/W2793146153","https://openalex.org/W2913535645","https://openalex.org/W2930684221","https://openalex.org/W2945291039","https://openalex.org/W2949440985","https://openalex.org/W2963528163","https://openalex.org/W2964204553","https://openalex.org/W2970295501","https://openalex.org/W2980868302","https://openalex.org/W2995286437","https://openalex.org/W2999778662","https://openalex.org/W3007179209","https://openalex.org/W3024822880","https://openalex.org/W3026405885","https://openalex.org/W3089464885","https://openalex.org/W3098883944","https://openalex.org/W3100075319","https://openalex.org/W3101311698","https://openalex.org/W3141595720","https://openalex.org/W3165612854","https://openalex.org/W4244393449","https://openalex.org/W4292363360","https://openalex.org/W4297979842","https://openalex.org/W6639824700","https://openalex.org/W6749271710","https://openalex.org/W6753088188","https://openalex.org/W6760969605","https://openalex.org/W6762438721","https://openalex.org/W6762492139","https://openalex.org/W6771619723","https://openalex.org/W6783257981"],"related_works":["https://openalex.org/W3156786002","https://openalex.org/W2738221750","https://openalex.org/W564581980","https://openalex.org/W4290238764","https://openalex.org/W2785438975","https://openalex.org/W2963735106","https://openalex.org/W3128305826","https://openalex.org/W2751100193","https://openalex.org/W2774444957","https://openalex.org/W3172319064"],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,27],"new":[3],"plug-and-play":[4],"priors":[5],"(PnP)":[6],"based":[7],"MR":[8,43],"image":[9],"reconstruction":[10],"method":[11,59,89],"that":[12,57],"systematically":[13],"enforces":[14],"data":[15,51],"consistency":[16],"while":[17],"also":[18,82],"exploiting":[19],"deep-learning":[20],"priors.":[21],"Our":[22],"prior":[23],"is":[24],"specified":[25],"through":[26],"convolutional":[28],"neural":[29],"network":[30],"(CNN)":[31],"trained":[32],"without":[33],"any":[34],"artifact-free":[35],"ground":[36],"truth":[37],"to":[38,70,91],"remove":[39],"under-sampling":[40],"artifacts":[41],"from":[42,65],"images.":[44],"The":[45,80],"results":[46,81],"on":[47],"reconstructing":[48],"free-breathing":[49],"MRI":[50],"into":[52],"ten":[53],"respiratory":[54],"phases":[55],"show":[56],"the":[58,84,88,96],"can":[60],"form":[61],"high-quality":[62],"4D":[63],"images":[64],"severely":[66],"undersampled":[67],"measurements":[68],"corresponding":[69],"acquisitions":[71],"of":[72,87],"about":[73],"1":[74],"and":[75,99],"2":[76],"minutes":[77],"in":[78],"length.":[79],"highlight":[83],"competitive":[85],"performance":[86],"compared":[90],"several":[92],"popular":[93],"alternatives,":[94],"including":[95],"TGV":[97],"regularization":[98],"traditional":[100],"UNet3D.":[101]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-04-07T14:57:38.498316","created_date":"2025-10-10T00:00:00"}
