iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: https://api.openalex.org/works/doi:10.1109/ISBI53787.2023.10230611
{"id":"https://openalex.org/W4386352903","doi":"https://doi.org/10.1109/isbi53787.2023.10230611","title":"Deep Reinforcement Learning Based Unrolling Network for MRI Reconstruction","display_name":"Deep Reinforcement Learning Based Unrolling Network for MRI Reconstruction","publication_year":2023,"publication_date":"2023-04-18","ids":{"openalex":"https://openalex.org/W4386352903","doi":"https://doi.org/10.1109/isbi53787.2023.10230611"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi53787.2023.10230611","pdf_url":null,"source":{"id":"https://openalex.org/S4363605129","display_name":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","issn_l":null,"issn":null,"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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5100329452","display_name":"Chong Wang","orcid":"https://orcid.org/0000-0002-7094-0466"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Chong Wang","raw_affiliation_strings":["Nanyang Technological University,School of Electrical & Electronic Engineering,Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University,School of Electrical & Electronic Engineering,Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090649169","display_name":"Rongkai Zhang","orcid":"https://orcid.org/0000-0002-0034-460X"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Rongkai Zhang","raw_affiliation_strings":["Nanyang Technological University,School of Electrical & Electronic Engineering,Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University,School of Electrical & Electronic Engineering,Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015073362","display_name":"Gabriel Maliakal","orcid":"https://orcid.org/0000-0002-0223-2732"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gabriel Maliakal","raw_affiliation_strings":["Dept. of Computational Mathematics, Science and Engineering, Michigan State University, MI, USA"],"affiliations":[{"raw_affiliation_string":"Dept. of Computational Mathematics, Science and Engineering, Michigan State University, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101799762","display_name":"Saiprasad Ravishankar","orcid":"https://orcid.org/0000-0002-5792-5827"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Saiprasad Ravishankar","raw_affiliation_strings":["Department of Biomedical Engineering, Michigan State University, East Lansing, MI, USA","Dept. of Computational Mathematics, Science and Engineering, Michigan State University, MI, USA"],"affiliations":[{"raw_affiliation_string":"Dept. of Computational Mathematics, Science and Engineering, Michigan State University, MI, USA","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Department of Biomedical Engineering, Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024709593","display_name":"Bihan Wen","orcid":"https://orcid.org/0000-0002-6874-6453"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Bihan Wen","raw_affiliation_strings":["Nanyang Technological University,School of Electrical & Electronic Engineering,Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University,School of Electrical & Electronic Engineering,Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.442,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.56557,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":69,"max":80},"biblio":{"volume":"32","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Theory and Applications of Compressed Sensing","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":"Theory and Applications of Compressed Sensing","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":"Magnetic Resonance Imaging Applications in Medicine","score":0.9999,"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/T12015","display_name":"Advances in Photoacoustic Imaging and Tomography","score":0.9995,"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/compressed-sensing","display_name":"Compressed Sensing","score":0.600889},{"id":"https://openalex.org/keywords/dictionary-learning","display_name":"Dictionary Learning","score":0.542399},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep Learning","score":0.54059},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic Resonance Imaging","score":0.527135},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex Optimization","score":0.502804},{"id":"https://openalex.org/keywords/loop-unrolling","display_name":"Loop unrolling","score":0.45147127}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7795604},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.72382927},{"id":"https://openalex.org/C136536468","wikidata":"https://www.wikidata.org/wiki/Q1225894","display_name":"Undersampling","level":2,"score":0.6424846},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5571494},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5334181},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.48349765},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47745898},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.46849495},{"id":"https://openalex.org/C76970557","wikidata":"https://www.wikidata.org/wiki/Q1869750","display_name":"Loop unrolling","level":3,"score":0.45147127},{"id":"https://openalex.org/C169590947","wikidata":"https://www.wikidata.org/wiki/Q47506","display_name":"Compiler","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi53787.2023.10230611","pdf_url":null,"source":{"id":"https://openalex.org/S4363605129","display_name":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","issn_l":null,"issn":null,"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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":20,"referenced_works":["https://openalex.org/W1794121648","https://openalex.org/W2100705753","https://openalex.org/W2101675075","https://openalex.org/W2156739854","https://openalex.org/W2304034118","https://openalex.org/W2552808051","https://openalex.org/W2573726823","https://openalex.org/W2736601468","https://openalex.org/W2778924750","https://openalex.org/W2970936390","https://openalex.org/W2997232065","https://openalex.org/W3035302306","https://openalex.org/W3092052495","https://openalex.org/W3100730608","https://openalex.org/W3195113607","https://openalex.org/W3206516528","https://openalex.org/W4200072838","https://openalex.org/W4205726274","https://openalex.org/W4250955649","https://openalex.org/W4308233882"],"related_works":["https://openalex.org/W3214931932","https://openalex.org/W3011226087","https://openalex.org/W2903019797","https://openalex.org/W2895530314","https://openalex.org/W2218273114","https://openalex.org/W2212041357","https://openalex.org/W2061033783","https://openalex.org/W2052082011","https://openalex.org/W1994141795","https://openalex.org/W1959447026"],"abstract_inverted_index":{"Compressed":[0],"sensing":[1],"(CS)":[2],"has":[3],"been":[4],"popular":[5],"in":[6,20,143],"magnetic":[7],"resonance":[8],"imaging":[9],"(MRI)":[10],"and":[11,25],"accelerates":[12],"the":[13,48,96,126,129,161,172,175,183,186,211],"measurement":[14],"acquisition":[15],"process":[16,164],"by":[17,146,156,181],"undersampling":[18],"data":[19],"k-space":[21],"while":[22,121],"exploiting":[23,182],"sparsity":[24],"incoherence":[26],"to":[27,54,70,79,85,103,108],"achieve":[28,55],"accurate":[29],"reconstructions.":[30],"Deep":[31],"learning":[32,68],"methods":[33,49,118],"have":[34],"recently":[35],"demonstrated":[36],"superior":[37,205],"performance":[38,208],"for":[39,136,168],"MRI":[40,169,206],"reconstruction":[41,207],"from":[42],"undersampled":[43],"data.":[44],"However,":[45,95],"most":[46,114],"of":[47,99,115,165,174,185],"rely":[50],"on":[51],"complex":[52],"models":[53],"promising":[56],"results":[57],"via":[58],"deterministic":[59],"optimization.":[60],"Alternatively,":[61],"very":[62],"recent":[63],"works":[64],"utilize":[65],"deep":[66],"reinforcement":[67],"(DRL)":[69],"restore":[71],"high-quality":[72],"images,":[73],"where":[74],"a":[75,91,151],"policy":[76],"is":[77,123,133,178],"learned":[78],"select":[80],"appropriate":[81],"actions":[82],"or":[83],"tools":[84],"progressively":[86],"refine":[87],"corrupted":[88],"images":[89],"with":[90,189,210],"simple":[92],"network":[93],"model.":[94],"model":[97,132,158,177],"capability":[98,173],"DRL-based":[100,153,201],"approaches":[101],"is,":[102],"some":[104],"extent,":[105],"limited":[106],"due":[107],"its":[109],"finite":[110],"action":[111],"space.":[112],"Moreover,":[113],"these":[116,147],"DRL":[117,166,176],"are":[119],"physics-free,":[120],"it":[122],"well-known":[124],"that":[125,198],"prior":[127],"concerning":[128],"physical":[130],"forward":[131],"extremely":[134],"crucial":[135],"solving":[137],"ill-posed":[138],"inverse":[139],"problems":[140],"such":[141],"as":[142],"CS-MRI.":[144],"Motivated":[145],"challenges,":[148],"we":[149],"propose":[150],"novel":[152],"unrolling":[154,187,202],"framework":[155,203],"integrating":[157],"priors":[159],"into":[160],"intrinsic":[162],"iterative":[163],"strategy":[167],"reconstruction.":[170],"Thus":[171],"significantly":[179],"enhanced":[180],"merits":[184],"scheme":[188],"almost":[190],"no":[191],"additional":[192],"computational":[193],"cost.":[194],"Extensive":[195],"experiments":[196],"demonstrate":[197],"our":[199],"proposed":[200],"achieves":[204],"compared":[209],"previous":[212],"baselines.":[213]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4386352903","counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2024-11-23T08:56:40.533180","created_date":"2023-09-02"}