{"id":"https://openalex.org/W4225015708","doi":"https://doi.org/10.1109/isbi52829.2022.9761711","title":"Deep Non-Linear Embedding Deformation Network for Cross-Modal Brain MRI Synthesis","display_name":"Deep Non-Linear Embedding Deformation Network for Cross-Modal Brain MRI Synthesis","publication_year":2022,"publication_date":"2022-03-28","ids":{"openalex":"https://openalex.org/W4225015708","doi":"https://doi.org/10.1109/isbi52829.2022.9761711"},"language":"en","primary_location":{"id":"doi:10.1109/isbi52829.2022.9761711","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi52829.2022.9761711","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 19th 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/A5104094924","display_name":"Yang Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Lin","raw_affiliation_strings":["University of Chinese Academy of Sciences,Beijing,China,100049"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences,Beijing,China,100049","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091049278","display_name":"Hu Han","orcid":"https://orcid.org/0000-0001-6010-1792"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"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/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hu Han","raw_affiliation_strings":["Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS),Institute of Computing Technology, CAS,Beijing,China,100190","University of Chinese Academy of Sciences, Beijing, China","Peng Cheng Laboratory, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS),Institute of Computing Technology, CAS,Beijing,China,100190","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]},{"raw_affiliation_string":"Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059801241","display_name":"S. Kevin Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"S. Kevin Zhou","raw_affiliation_strings":["Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS),Institute of Computing Technology, CAS,Beijing,China,100190","Medical Imaging, Robotics, and Analytic Computing Laboratory and Engineering (MIRACLE), School of Biomedical Engineering & Suzhou Institute for Advance Research, University of Science and Technology of China, Suzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS),Institute of Computing Technology, CAS,Beijing,China,100190","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"raw_affiliation_string":"Medical Imaging, Robotics, and Analytic Computing Laboratory and Engineering (MIRACLE), School of Biomedical Engineering & Suzhou Institute for Advance Research, University of Science and Technology of China, Suzhou, China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9976999759674072,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9976999759674072,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.995199978351593,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.829936146736145},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6379553079605103},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.5980916619300842},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5593633651733398},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5399238467216492},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.5313347578048706},{"id":"https://openalex.org/keywords/fluid-attenuated-inversion-recovery","display_name":"Fluid-attenuated inversion recovery","score":0.493962824344635},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.4234279990196228},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4150877594947815},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35383129119873047},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.2404840886592865},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.14176958799362183}],"concepts":[{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.829936146736145},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6379553079605103},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.5980916619300842},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5593633651733398},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5399238467216492},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.5313347578048706},{"id":"https://openalex.org/C101070640","wikidata":"https://www.wikidata.org/wiki/Q3737215","display_name":"Fluid-attenuated inversion recovery","level":3,"score":0.493962824344635},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.4234279990196228},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4150877594947815},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35383129119873047},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.2404840886592865},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.14176958799362183},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi52829.2022.9761711","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi52829.2022.9761711","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8199999928474426,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320335892","display_name":"Youth Innovation Promotion Association","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1605218991","https://openalex.org/W1983060851","https://openalex.org/W2015897296","https://openalex.org/W2060405238","https://openalex.org/W2100495482","https://openalex.org/W2110966329","https://openalex.org/W2807246925","https://openalex.org/W2914057844","https://openalex.org/W2963073614","https://openalex.org/W2963768110","https://openalex.org/W2964024004","https://openalex.org/W3007486523","https://openalex.org/W3089567139","https://openalex.org/W3093276592","https://openalex.org/W3118835302","https://openalex.org/W3165358499","https://openalex.org/W6665754546"],"related_works":["https://openalex.org/W73545470","https://openalex.org/W4224266612","https://openalex.org/W2383394264","https://openalex.org/W4320153225","https://openalex.org/W4293261942","https://openalex.org/W3125968744","https://openalex.org/W2167701463","https://openalex.org/W2110287964","https://openalex.org/W4307407935","https://openalex.org/W649759291"],"abstract_inverted_index":{"Multimodal":[0],"MRI":[1,22,47,52,66,109,152],"(e.g.":[2],"T1,":[3],"T2,":[4],"and":[5,11,18,87,124,141],"Flair)":[6],"can":[7,159],"provide":[8],"rich":[9],"anatomical":[10,86],"functional":[12],"information,":[13],"thereby":[14],"facilitating":[15],"clinical":[16,59],"diagnosis":[17],"treatment.":[19],"However,":[20],"multimodal":[21],"takes":[23],"a":[24,45,50,99,116,126],"long":[25],"scan":[26],"time,":[27],"easily":[28],"leading":[29,83],"to":[30,43,54,84,132],"artifacts":[31],"or":[32],"corruption":[33],"in":[34,90],"certain":[35],"modalities.":[36,137],"Therefore,":[37],"it":[38],"is":[39,130],"of":[40,76],"great":[41],"value":[42],"synthesize":[44],"new":[46,151],"modality":[48,53,114],"from":[49],"complete":[51],"obtain":[55,160],"complementary":[56],"information":[57],"for":[58,106,148],"diagnosis.":[60],"Existing":[61],"GAN-based":[62],"approaches":[63],"treat":[64],"cross-modal":[65,107],"synthesis":[67,163],"as":[68,115],"an":[69],"end-to-end":[70],"learning":[71],"process":[72],"without":[73],"explicit":[74],"consideration":[75],"the":[77,91,134,150],"inherent":[78],"correlations":[79],"between":[80],"different":[81],"modalities,":[82],"inaccurate":[85],"lesion":[88],"structure":[89],"synthesized":[92],"modality.":[93,153],"In":[94],"this":[95],"paper,":[96],"we":[97],"propose":[98],"deep":[100],"non-linear":[101,117],"embedding":[102,118],"deformation":[103,127,144],"network":[104],"(NEDNet)":[105],"brain":[108],"synthesis.":[110],"NEDNet":[111],"represents":[112],"each":[113],"based":[119],"w.r.t.":[120],"its":[121],"own":[122],"atlas,":[123],"learns":[125],"feature":[128],"that":[129,156],"assumed":[131],"be":[133],"same":[135],"across":[136],"The":[138],"modality-specific":[139],"atlas":[140],"multi-modal":[142],"shared":[143],"are":[145],"jointly":[146],"used":[147],"generating":[149],"Experiments":[154],"show":[155],"our":[157],"approach":[158],"better":[161],"cross-modality":[162],"results":[164],"than":[165],"several":[166],"baseline":[167],"methods.":[168]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}