{"id":"https://openalex.org/W4388107585","doi":"https://doi.org/10.1109/tci.2023.3328281","title":"MD-GraphFormer: A Model-Driven Graph Transformer for Fast Multi-Contrast MR Imaging","display_name":"MD-GraphFormer: A Model-Driven Graph Transformer for Fast Multi-Contrast MR Imaging","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4388107585","doi":"https://doi.org/10.1109/tci.2023.3328281"},"language":"en","primary_location":{"id":"doi:10.1109/tci.2023.3328281","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tci.2023.3328281","pdf_url":null,"source":{"id":"https://openalex.org/S4210233665","display_name":"IEEE Transactions on Computational Imaging","issn_l":"2333-9403","issn":["2333-9403","2334-0118","2573-0436"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Imaging","raw_type":"journal-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/A5103275853","display_name":"Jiazhen Wang","orcid":"https://orcid.org/0000-0003-3226-349X"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiazhen Wang","raw_affiliation_strings":["School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0003-3226-349X","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101785878","display_name":"Yan Yang","orcid":"https://orcid.org/0000-0001-6227-5235"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Yang","raw_affiliation_strings":["School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0001-6227-5235","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101882968","display_name":"Heran Yang","orcid":"https://orcid.org/0000-0002-3430-4761"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heran Yang","raw_affiliation_strings":["School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0002-3430-4761","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077300873","display_name":"Chunfeng Lian","orcid":"https://orcid.org/0000-0002-9319-6633"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunfeng Lian","raw_affiliation_strings":["School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0002-9319-6633","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zongben Xu","orcid":"https://orcid.org/0000-0003-1719-3358"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]},{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongben Xu","raw_affiliation_strings":["School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China","Pazhou Lab (Huangpu) and Peng Cheng Lab, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0003-1719-3358","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"Pazhou Lab (Huangpu) and Peng Cheng Lab, Guangdong, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037419606","display_name":"Jian Sun","orcid":"https://orcid.org/0000-0001-7206-0641"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]},{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Sun","raw_affiliation_strings":["School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China","Pazhou Lab (Huangpu) and Peng Cheng Lab, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0001-7206-0641","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"Pazhou Lab (Huangpu) and Peng Cheng Lab, Guangdong, China","institution_ids":["https://openalex.org/I4210136793"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.7026,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.90596341,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"9","issue":null,"first_page":"1018","last_page":"1030"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9993000030517578,"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/T11885","display_name":"MRI in cancer diagnosis","score":0.9991999864578247,"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/contrast","display_name":"Contrast (vision)","score":0.6810530424118042},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6296262741088867},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6100830435752869},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5485667586326599},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.5401858687400818},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4923175573348999},{"id":"https://openalex.org/keywords/real-time-mri","display_name":"Real-time MRI","score":0.4493841528892517},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.44333186745643616},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41086822748184204},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.13199785351753235},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.10660314559936523},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.0955742597579956}],"concepts":[{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.6810530424118042},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6296262741088867},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6100830435752869},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5485667586326599},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.5401858687400818},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4923175573348999},{"id":"https://openalex.org/C157787499","wikidata":"https://www.wikidata.org/wiki/Q13479657","display_name":"Real-time MRI","level":3,"score":0.4493841528892517},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.44333186745643616},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41086822748184204},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.13199785351753235},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.10660314559936523},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0955742597579956}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tci.2023.3328281","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tci.2023.3328281","pdf_url":null,"source":{"id":"https://openalex.org/S4210233665","display_name":"IEEE Transactions on Computational Imaging","issn_l":"2333-9403","issn":["2333-9403","2334-0118","2573-0436"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Imaging","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.46000000834465027,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G3056973599","display_name":"\u6269\u6563\u6a21\u578b\u9a71\u52a8\u7684\u56fe\u7ed3\u6784\u6df1\u5ea6\u5b66\u4e60\u65b9\u6cd5\u53ca\u5176\u5e94\u7528\u7814\u7a76","funder_award_id":"11971373","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4419852451","display_name":null,"funder_award_id":"12125104","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G575329728","display_name":null,"funder_award_id":"U20B2075","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G824516698","display_name":null,"funder_award_id":"12090021","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1972898607","https://openalex.org/W2047544187","https://openalex.org/W2115706991","https://openalex.org/W2117649283","https://openalex.org/W2134884567","https://openalex.org/W2136334171","https://openalex.org/W2141168890","https://openalex.org/W2155893237","https://openalex.org/W2163973643","https://openalex.org/W2281493160","https://openalex.org/W2442117232","https://openalex.org/W2494581537","https://openalex.org/W2552808051","https://openalex.org/W2604388535","https://openalex.org/W2752782242","https://openalex.org/W2773850766","https://openalex.org/W2796670799","https://openalex.org/W2798559986","https://openalex.org/W2883105305","https://openalex.org/W2891888042","https://openalex.org/W2902719825","https://openalex.org/W2949402056","https://openalex.org/W2950936580","https://openalex.org/W2962903101","https://openalex.org/W2964545333","https://openalex.org/W2998376473","https://openalex.org/W3009994569","https://openalex.org/W3034546843","https://openalex.org/W3035596626","https://openalex.org/W3046934520","https://openalex.org/W3080851077","https://openalex.org/W3091193055","https://openalex.org/W3094502228","https://openalex.org/W3100694778","https://openalex.org/W3100730608","https://openalex.org/W3101674918","https://openalex.org/W3119151570","https://openalex.org/W3125077400","https://openalex.org/W3138516171","https://openalex.org/W4223589960","https://openalex.org/W4225672218","https://openalex.org/W4282976788","https://openalex.org/W4296057693","https://openalex.org/W4319300853","https://openalex.org/W4385245566","https://openalex.org/W6639824700","https://openalex.org/W6729455701","https://openalex.org/W6739901393","https://openalex.org/W6784333009"],"related_works":["https://openalex.org/W3080267150","https://openalex.org/W2756957295","https://openalex.org/W4385543058","https://openalex.org/W4293253204","https://openalex.org/W1996797998","https://openalex.org/W2995582197","https://openalex.org/W2998746225","https://openalex.org/W1969553609","https://openalex.org/W2111027377","https://openalex.org/W2613073969"],"abstract_inverted_index":{"In":[0,46],"magnetic":[1],"resonance":[2],"imaging":[3,27,168],"(MRI),":[4],"multi-contrast":[5,25,43,58,74,92,104,122,162],"pulse":[6],"sequences":[7],"are":[8,133],"routinely":[9],"acquired,":[10],"providing":[11],"complementary":[12,40,71],"information":[13,41,72],"for":[14,56],"medical":[15],"diagnosis.":[16],"Compared":[17],"with":[18,110],"the":[19,24,39,63,70,101,108,117,120,136,156,160],"single-contrast":[20],"MR":[21,26,44,59,75,105,113,123],"image":[22],"reconstruction,":[23],"could":[28],"further":[29],"accelerate":[30],"data":[31,93],"acquisition":[32],"and":[33,68,80,91,99,125,140,149],"improve":[34],"reconstruction":[35,164],"quality":[36],"by":[37],"leveraging":[38],"of":[42,66,86,103],"images.":[45],"this":[47],"paper,":[48],"we":[49],"propose":[50],"a":[51],"model-driven":[52],"graph":[53,78,109],"transformer":[54],"(MD-GraphFormer)":[55],"fast":[57],"imaging,":[60],"which":[61],"incorporates":[62],"physical":[64],"constraints":[65],"MRI":[67,143,163],"investigates":[69],"among":[73],"images":[76,106,124],"using":[77],"structure":[79],"attention":[81],"mechanism.":[82],"The":[83,152],"MD-GraphFormer":[84,158],"consists":[85],"graph-attention-based":[87],"interaction":[88],"modules":[89,95],"(GAB-IM)":[90],"consistency":[94,118],"(MC-DCM).":[96],"GAB-IM":[97],"learns":[98],"interacts":[100],"features":[102],"over":[107],"nodes":[111],"representing":[112],"contrasts.":[114],"MC-DCM":[115],"enforces":[116],"between":[119],"reconstructed":[121],"their":[126],"corresponding":[127],"measurements":[128],"in":[129,166],"k-space.":[130],"Extensive":[131],"experiments":[132],"conducted":[134],"on":[135],"collected":[137],"raw":[138],"uMR":[139],"SMS":[141],"brain":[142],"datasets":[144],"under":[145],"different":[146],"sampling":[147,150],"patterns":[148],"rates.":[151],"results":[153],"demonstrate":[154],"that":[155],"proposed":[157],"outperforms":[159],"previous":[161],"methods":[165],"multi-coil":[167],"settings.":[169]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}