{"id":"https://openalex.org/W4386362598","doi":"https://doi.org/10.1109/isbi53787.2023.10230600","title":"ViGU: Vision GNN U-Net for fast MRI","display_name":"ViGU: Vision GNN U-Net for fast MRI","publication_year":2023,"publication_date":"2023-04-18","ids":{"openalex":"https://openalex.org/W4386362598","doi":"https://doi.org/10.1109/isbi53787.2023.10230600"},"language":"en","primary_location":{"id":"doi:10.1109/isbi53787.2023.10230600","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi53787.2023.10230600","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101871868","display_name":"Jiahao Huang","orcid":"https://orcid.org/0000-0002-0880-0446"},"institutions":[{"id":"https://openalex.org/I4210096640","display_name":"Royal Brompton Hospital","ror":"https://ror.org/00cv4n034","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I2800036501","https://openalex.org/I4210096640"]},{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jiahao Huang","raw_affiliation_strings":["National Heart and Lung Institute,Imperial College,London,United Kingdom","Imperial College, National Heart and Lung Institute, London, United Kingdom","Royal Brompton Hospital, Cardiovascular Research Centre, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Heart and Lung Institute,Imperial College,London,United Kingdom","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"Imperial College, National Heart and Lung Institute, London, United Kingdom","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"Royal Brompton Hospital, Cardiovascular Research Centre, United Kingdom","institution_ids":["https://openalex.org/I4210096640"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013015879","display_name":"Angelica I. Avil\u00e9s-Rivero","orcid":"https://orcid.org/0000-0002-8878-0325"},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Angelica I. Aviles-Rivero","raw_affiliation_strings":["University of Cambridge,Department of Applied Mathematics and Theoretical Physics,United Kingdom","Department of Applied Mathematics and Theoretical Physics, University of Cambridge, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Cambridge,Department of Applied Mathematics and Theoretical Physics,United Kingdom","institution_ids":["https://openalex.org/I241749"]},{"raw_affiliation_string":"Department of Applied Mathematics and Theoretical Physics, University of Cambridge, United Kingdom","institution_ids":["https://openalex.org/I241749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033880300","display_name":"Carola\u2010Bibiane Sch\u00f6nlieb","orcid":"https://orcid.org/0000-0003-0099-6306"},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Carola-Bibiane Sch\u00f6nlieb","raw_affiliation_strings":["University of Cambridge,Department of Applied Mathematics and Theoretical Physics,United Kingdom","Department of Applied Mathematics and Theoretical Physics, University of Cambridge, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Cambridge,Department of Applied Mathematics and Theoretical Physics,United Kingdom","institution_ids":["https://openalex.org/I241749"]},{"raw_affiliation_string":"Department of Applied Mathematics and Theoretical Physics, University of Cambridge, United Kingdom","institution_ids":["https://openalex.org/I241749"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100436460","display_name":"Guang Yang","orcid":"https://orcid.org/0000-0001-7344-7733"},"institutions":[{"id":"https://openalex.org/I4210096640","display_name":"Royal Brompton Hospital","ror":"https://ror.org/00cv4n034","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I2800036501","https://openalex.org/I4210096640"]},{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Guang Yang","raw_affiliation_strings":["National Heart and Lung Institute,Imperial College,London,United Kingdom","Imperial College, National Heart and Lung Institute, London, United Kingdom","Royal Brompton Hospital, Cardiovascular Research Centre, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Heart and Lung Institute,Imperial College,London,United Kingdom","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"Imperial College, National Heart and Lung Institute, London, United Kingdom","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"Royal Brompton Hospital, Cardiovascular Research Centre, United Kingdom","institution_ids":["https://openalex.org/I4210096640"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.578,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.89280528,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9969000220298767,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7806172370910645},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6113035678863525},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5750089883804321},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5075644254684448},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4865245223045349},{"id":"https://openalex.org/keywords/euclidean-geometry","display_name":"Euclidean geometry","score":0.44994041323661804},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.42767566442489624},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4247402846813202},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.424331396818161},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41922739148139954},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35198402404785156},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3362503945827484},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2786722183227539},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11319738626480103}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7806172370910645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6113035678863525},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5750089883804321},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5075644254684448},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4865245223045349},{"id":"https://openalex.org/C129782007","wikidata":"https://www.wikidata.org/wiki/Q162886","display_name":"Euclidean geometry","level":2,"score":0.44994041323661804},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.42767566442489624},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4247402846813202},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.424331396818161},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41922739148139954},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35198402404785156},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3362503945827484},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2786722183227539},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11319738626480103},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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":[{"id":"doi:10.1109/isbi53787.2023.10230600","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi53787.2023.10230600","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1424764954","display_name":null,"funder_award_id":"EP/T017961/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G1755984640","display_name":null,"funder_award_id":"EP/N014588/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G207202694","display_name":null,"funder_award_id":"MC_PC_21013","funder_id":"https://openalex.org/F4320334626","funder_display_name":"Medical Research Council"},{"id":"https://openalex.org/G7243674615","display_name":null,"funder_award_id":"EP/V029428/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320320006","display_name":"Royal Society","ror":"https://ror.org/03wnrjx87"},{"id":"https://openalex.org/F4320334626","display_name":"Medical Research Council","ror":"https://ror.org/03x94j517"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2552808051","https://openalex.org/W2594014149","https://openalex.org/W2742774307","https://openalex.org/W2778924750","https://openalex.org/W2990045899","https://openalex.org/W3035687950","https://openalex.org/W3094502228","https://openalex.org/W3203262038","https://openalex.org/W4200631312","https://openalex.org/W4210305140","https://openalex.org/W4221148807","https://openalex.org/W4223589960","https://openalex.org/W4284896652","https://openalex.org/W4301206121","https://openalex.org/W4320167334","https://openalex.org/W6729455701","https://openalex.org/W6765779288","https://openalex.org/W6784333009","https://openalex.org/W6804681083","https://openalex.org/W6848935878"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4375867731","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W4389345324"],"abstract_inverted_index":{"Deep":[0],"learning":[1,15],"models":[2,51],"have":[3],"been":[4],"widely":[5],"applied":[6],"for":[7,77],"fast":[8,78],"MRI.":[9],"The":[10,198],"majority":[11],"of":[12,49,174,183],"existing":[13,50,151],"deep":[14],"models,":[16],"e.g.,":[17],"convolutional":[18],"neural":[19],"networks,":[20],"work":[21],"on":[22,168],"data":[23,36,53],"with":[24,165],"Euclidean":[25],"or":[26],"regular":[27],"grids":[28],"structures.":[29],"However,":[30],"high-dimensional":[31],"features":[32,62,191],"extracted":[33],"from":[34,127,192],"MR":[35,64,193],"could":[37],"be":[38],"encapsulated":[39],"in":[40,63,111],"non-Euclidean":[41],"manifolds.":[42],"This":[43],"disparity":[44],"between":[45],"the":[46,56,87,121,144,160,175,180,184,188],"go-to":[47],"assumption":[48],"and":[52,95,114,140,147,153],"requirements":[54],"limits":[55],"flexibility":[57],"to":[58,132],"capture":[59],"irregular":[60],"anatomical":[61],"data.":[65],"In":[66],"this":[67],"work,":[68],"we":[69,118,157],"introduce":[70],"a":[71,99,102,172],"novel":[72],"Vision":[73,81],"GNN":[74,82],"type":[75],"network":[76,104,162,185,189],"MRI":[79],"called":[80],"U-Net":[83],"(ViGU).":[84],"More":[85,178],"precisely,":[86],"pixel":[88],"array":[89],"is":[90,105,200],"first":[91],"embedded":[92],"into":[93,98],"patches":[94],"then":[96],"converted":[97],"graph.":[100],"Secondly,":[101],"U-shape":[103],"developed":[106],"using":[107],"several":[108],"graph":[109,181],"blocks":[110],"symmetrical":[112],"encoder":[113],"decoder":[115],"paths.":[116],"Moreover,":[117,156],"show":[119,158],"that":[120,143,159],"proposed":[122,145,161],"ViGU":[123,146],"can":[124],"also":[125],"benefit":[126],"Generative":[128],"Adversarial":[129],"Networks":[130],"yielding":[131],"its":[133],"variant":[134,149],"ViGU-GAN.":[135],"We":[136],"demonstrate,":[137],"through":[138],"numerical":[139],"visual":[141],"experiments,":[142],"GAN":[148],"outperform":[150],"CNN":[152],"GAN-based":[154],"methods.":[155],"readily":[163],"competes":[164],"approaches":[166],"based":[167],"Transformers":[169],"while":[170],"requiring":[171],"fraction":[173],"computational":[176],"cost.":[177],"importantly,":[179],"structure":[182],"reveals":[186],"how":[187],"extracts":[190],"images,":[194],"providing":[195],"intuitive":[196],"explainability.":[197],"code":[199],"publicly":[201],"available":[202],"at":[203],"https://github.com/ayanglab/ViGU.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
