{"id":"https://openalex.org/W4390971065","doi":"https://doi.org/10.1109/bibm58861.2023.10385266","title":"AVS-Net: Attention-based Variable Splitting Network for P-MRI Acceleration","display_name":"AVS-Net: Attention-based Variable Splitting Network for P-MRI Acceleration","publication_year":2023,"publication_date":"2023-12-05","ids":{"openalex":"https://openalex.org/W4390971065","doi":"https://doi.org/10.1109/bibm58861.2023.10385266"},"language":"en","primary_location":{"id":"doi:10.1109/bibm58861.2023.10385266","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm58861.2023.10385266","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5100333704","display_name":"Yue Zhang","orcid":"https://orcid.org/0000-0002-2868-9941"},"institutions":[{"id":"https://openalex.org/I79619799","display_name":"University of Birmingham","ror":"https://ror.org/03angcq70","country_code":"GB","type":"education","lineage":["https://openalex.org/I79619799"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yue Zhang","raw_affiliation_strings":["University of Birmingham,School of Computer Science,Birmingham,UK","School of Computer Science, University of Birmingham, Birmingham, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Birmingham,School of Computer Science,Birmingham,UK","institution_ids":["https://openalex.org/I79619799"]},{"raw_affiliation_string":"School of Computer Science, University of Birmingham, Birmingham, UK","institution_ids":["https://openalex.org/I79619799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100367178","display_name":"Jing Li","orcid":"https://orcid.org/0000-0001-9654-4536"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Li","raw_affiliation_strings":["Tsinghua University,School of Economics and Management,Beijing,China","School of Economics and Management, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,School of Economics and Management,Beijing,China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"School of Economics and Management, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055798998","display_name":"Zigan Wang","orcid":"https://orcid.org/0000-0002-1311-1493"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zigan Wang","raw_affiliation_strings":["Tsinghua University,Shenzhen International Graduate School,Shenzhen,China","Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Shenzhen International Graduate School,Shenzhen,China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078754523","display_name":"Jinming Duan","orcid":"https://orcid.org/0000-0002-5108-2128"},"institutions":[{"id":"https://openalex.org/I79619799","display_name":"University of Birmingham","ror":"https://ror.org/03angcq70","country_code":"GB","type":"education","lineage":["https://openalex.org/I79619799"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jinming Duan","raw_affiliation_strings":["University of Birmingham,School of Computer Science,Birmingham,UK","School of Computer Science, University of Birmingham, Birmingham, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Birmingham,School of Computer Science,Birmingham,UK","institution_ids":["https://openalex.org/I79619799"]},{"raw_affiliation_string":"School of Computer Science, University of Birmingham, Birmingham, UK","institution_ids":["https://openalex.org/I79619799"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110488978","display_name":"Jinliang Li","orcid":"https://orcid.org/0000-0002-2200-5123"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinliang Li","raw_affiliation_strings":["Tsinghua University,School of Economics and Management,Beijing,China","School of Economics and Management, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,School of Economics and Management,Beijing,China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"School of Economics and Management, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6579,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.73293876,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1682","last_page":"1689"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":1.0,"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":1.0,"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":0.9994999766349792,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.996999979019165,"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":0.7834558486938477},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.6147875189781189},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5870183706283569},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.5077532529830933},{"id":"https://openalex.org/keywords/data-consistency","display_name":"Data consistency","score":0.4358830153942108},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.43082961440086365},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42887240648269653},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4021960496902466},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3221225142478943}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7834558486938477},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.6147875189781189},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5870183706283569},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5077532529830933},{"id":"https://openalex.org/C93361087","wikidata":"https://www.wikidata.org/wiki/Q4426698","display_name":"Data consistency","level":2,"score":0.4358830153942108},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.43082961440086365},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42887240648269653},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4021960496902466},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3221225142478943},{"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/bibm58861.2023.10385266","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm58861.2023.10385266","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320337986","display_name":"Tsinghua Shenzhen International Graduate School","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W2047544187","https://openalex.org/W2442117232","https://openalex.org/W2594014149","https://openalex.org/W2604388535","https://openalex.org/W2611467245","https://openalex.org/W2795380527","https://openalex.org/W2979793468","https://openalex.org/W3094502228","https://openalex.org/W3137984567","https://openalex.org/W3138516171","https://openalex.org/W3157723514","https://openalex.org/W3172509117","https://openalex.org/W3186314696","https://openalex.org/W3193873731","https://openalex.org/W3202624106","https://openalex.org/W3202833871","https://openalex.org/W3214344246","https://openalex.org/W4223560357","https://openalex.org/W4223589960","https://openalex.org/W4226205381","https://openalex.org/W4294975511","https://openalex.org/W4313526632","https://openalex.org/W4403090845","https://openalex.org/W6739901393","https://openalex.org/W6780226713","https://openalex.org/W6784333009","https://openalex.org/W6799920274","https://openalex.org/W6810032263","https://openalex.org/W6810101649","https://openalex.org/W6810748513","https://openalex.org/W6842549772","https://openalex.org/W6931779256"],"related_works":["https://openalex.org/W2158224665","https://openalex.org/W2379589510","https://openalex.org/W2810730439","https://openalex.org/W4300044672","https://openalex.org/W1881631164","https://openalex.org/W2358292267","https://openalex.org/W2378166785","https://openalex.org/W1964277756","https://openalex.org/W2896778670","https://openalex.org/W3118674572"],"abstract_inverted_index":{"Reconstructing":[0],"undersampled":[1],"medical":[2],"images":[3],"from":[4],"k-space":[5,86],"magnetic":[6],"resonance":[7],"imaging":[8],"(MRI)":[9],"data":[10,87,114],"with":[11,110,123,132,143,151],"multi-coil":[12],"acquisitions":[13],"is":[14,178],"a":[15,27,60,79,129,148],"major":[16],"challenge":[17],"for":[18,31,88],"deep":[19],"learning":[20],"algorithms.":[21],"Applying":[22],"convolutional":[23],"architecture":[24],"has":[25],"become":[26],"widely":[28],"used":[29],"framework":[30],"reconstructing":[32],"MR":[33,126],"images.":[34,127],"It":[35],"offers":[36],"excellent":[37],"performance":[38],"but":[39],"causes":[40],"signal":[41],"synthesis":[42],"and":[43,76,101,118,121,158],"artifact":[44],"compensation":[45],"concerns":[46],"due":[47],"to":[48,134,147,174],"the":[49,89,136,154,161],"limitations":[50],"of":[51,82,141],"local":[52],"receptive":[53],"fields.":[54],"Inspired":[55],"by":[56],"Transformers,":[57],"we":[58],"propose":[59],"novel":[61],"Attention-based":[62],"Variable":[63],"MRI":[64,113],"reconstruction":[65,92,103,170],"Splitting":[66],"Network":[67],"termed":[68],"AVS-Net,":[69],"whose":[70],"features":[71],"are":[72],"expressed":[73],"as":[74],"keys":[75],"queries,":[77],"capturing":[78],"wider":[80],"range":[81],"relations":[83],"among":[84],"parallel":[85,102],"compressed":[90],"sensing":[91],"problem.":[93],"AVSNet":[94],"overcomes":[95],"two":[96],"challenges":[97],"in":[98,115],"visual":[99],"tokenization":[100],"pixel":[104],"consistency.":[105],"The":[106,176],"model":[107],"was":[108],"trained":[109],"400":[111,124],"knee":[112,125],"40":[116],"slices":[117],"15":[119],"channels":[120],"tested":[122],"As":[128],"quantitative":[130],"result":[131],"respect":[133],"PSNR,":[135,156],"training":[137],"achieved":[138],"an":[139],"average":[140],"39.46":[142],"default":[144],"parameters,":[145],"compared":[146,173],"6.8%":[149],"increase":[150],"SOTA.":[152,175],"Combining":[153],"NMSE,":[155],"SSIM,":[157],"MSE":[159],"metrics,":[160],"numerical":[162],"results":[163],"show":[164],"that":[165],"our":[166],"method":[167],"provides":[168],"better":[169],"perceptual":[171],"quality":[172],"code":[177],"publicly":[179],"available":[180],"at":[181],"https://github.com/AVS-Net/AVS-Net.":[182]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}