{"id":"https://openalex.org/W4401990391","doi":"https://doi.org/10.1109/tci.2024.3452008","title":"Implicit Neural Networks With Fourier-Feature Inputs for Free-Breathing Cardiac MRI Reconstruction","display_name":"Implicit Neural Networks With Fourier-Feature Inputs for Free-Breathing Cardiac MRI Reconstruction","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4401990391","doi":"https://doi.org/10.1109/tci.2024.3452008"},"language":"en","primary_location":{"id":"doi:10.1109/tci.2024.3452008","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tci.2024.3452008","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/A5048870691","display_name":"Johannes F. Kunz","orcid":"https://orcid.org/0009-0006-9955-6405"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Johannes F. Kunz","raw_affiliation_strings":["Department of Computer Engineering, Technical University of Munich, M&#x00FC;nchen, Germany"],"raw_orcid":"https://orcid.org/0009-0006-9955-6405","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Technical University of Munich, M&#x00FC;nchen, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074658986","display_name":"Stefan Ruschke","orcid":"https://orcid.org/0000-0001-9658-6541"},"institutions":[{"id":"https://openalex.org/I2802619606","display_name":"TUM Klinikum","ror":"https://ror.org/04jc43x05","country_code":"DE","type":"healthcare","lineage":["https://openalex.org/I2802619606","https://openalex.org/I62916508"]},{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Stefan Ruschke","raw_affiliation_strings":["Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, M&#x00FC;nchen, Germany"],"raw_orcid":"https://orcid.org/0000-0001-9658-6541","affiliations":[{"raw_affiliation_string":"Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, M&#x00FC;nchen, Germany","institution_ids":["https://openalex.org/I2802619606","https://openalex.org/I62916508"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003606899","display_name":"Reinhard Heckel","orcid":"https://orcid.org/0000-0002-2874-2984"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Reinhard Heckel","raw_affiliation_strings":["Department of Computer Engineering, Technical University of Munich, M&#x00FC;nchen, Germany"],"raw_orcid":"https://orcid.org/0000-0002-2874-2984","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Technical University of Munich, M&#x00FC;nchen, Germany","institution_ids":["https://openalex.org/I62916508"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":15.7269,"has_fulltext":false,"cited_by_count":47,"citation_normalized_percentile":{"value":0.99474004,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"10","issue":null,"first_page":"1280","last_page":"1289"},"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/T11993","display_name":"Atomic and Subatomic Physics Research","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9988999962806702,"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/artificial-neural-network","display_name":"Artificial neural network","score":0.5813785195350647},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5777862071990967},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5748971104621887},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5736583471298218},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.5560624599456787},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.5527144074440002},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5479845404624939},{"id":"https://openalex.org/keywords/fourier-analysis","display_name":"Fourier analysis","score":0.47031059861183167},{"id":"https://openalex.org/keywords/real-time-mri","display_name":"Real-time MRI","score":0.43196722865104675},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42302757501602173},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.3274233937263489},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24831196665763855},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.21977218985557556},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.18985119462013245}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5813785195350647},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5777862071990967},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5748971104621887},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5736583471298218},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.5560624599456787},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5527144074440002},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5479845404624939},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.47031059861183167},{"id":"https://openalex.org/C157787499","wikidata":"https://www.wikidata.org/wiki/Q13479657","display_name":"Real-time MRI","level":3,"score":0.43196722865104675},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42302757501602173},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.3274233937263489},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24831196665763855},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.21977218985557556},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.18985119462013245},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tci.2024.3452008","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tci.2024.3452008","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":[{"id":"https://metadata.un.org/sdg/2","score":0.5299999713897705,"display_name":"Zero hunger"}],"awards":[{"id":"https://openalex.org/G2678052068","display_name":"Theorie und Praxis von nicht Trainierten Neuronalen Netzwerken","funder_award_id":"456465471","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G3211418997","display_name":"Deep Learning f\u00fcr die Bildgebung von nichtstatischen Objekten","funder_award_id":"517586365","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G6188494235","display_name":"L\u00f6sungsverfahren f\u00fcr inverse Probleme basierend auf neuronalen Netzen: Expressivit\u00e4t, Generalisierung und Robustheit","funder_award_id":"464123524","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1482297123","https://openalex.org/W2039325635","https://openalex.org/W2098833891","https://openalex.org/W2146481498","https://openalex.org/W2156739854","https://openalex.org/W2211925052","https://openalex.org/W2594014149","https://openalex.org/W2726168645","https://openalex.org/W2762336051","https://openalex.org/W2771305881","https://openalex.org/W2797196654","https://openalex.org/W2912009603","https://openalex.org/W2916033043","https://openalex.org/W2922528425","https://openalex.org/W2962734274","https://openalex.org/W3015567121","https://openalex.org/W3039473929","https://openalex.org/W3042031351","https://openalex.org/W3048384642","https://openalex.org/W3104724358","https://openalex.org/W3109585842","https://openalex.org/W3139209939","https://openalex.org/W3163954017","https://openalex.org/W3180415281","https://openalex.org/W3184682426","https://openalex.org/W3188455524","https://openalex.org/W3195875706","https://openalex.org/W3202371506","https://openalex.org/W4224274250","https://openalex.org/W4226066657","https://openalex.org/W4281651265","https://openalex.org/W4306995891","https://openalex.org/W4312480149","https://openalex.org/W4313483476","https://openalex.org/W4379660302","https://openalex.org/W4386075614","https://openalex.org/W4386076557","https://openalex.org/W6755694737","https://openalex.org/W6770190274","https://openalex.org/W6779358743","https://openalex.org/W6779753539","https://openalex.org/W6780179280","https://openalex.org/W6848925088","https://openalex.org/W6888459092"],"related_works":["https://openalex.org/W1984031140","https://openalex.org/W2034082304","https://openalex.org/W81470468","https://openalex.org/W1964268922","https://openalex.org/W1968864649","https://openalex.org/W2066908446","https://openalex.org/W2768366820","https://openalex.org/W2015885629","https://openalex.org/W1971280405","https://openalex.org/W2033702064"],"abstract_inverted_index":{"Cardiacmagnetic":[0],"resonance":[1],"imaging":[2],"(MRI)":[3],"requires":[4],"reconstructing":[5],"a":[6,10,41,77,153,169,192],"real-time":[7,114],"video":[8],"of":[9,63,76,102,195],"beating":[11,48],"heart":[12,49,65],"from":[13],"continuous":[14],"highly":[15],"under-sampled":[16],"measurements.":[17,70,164],"This":[18],"task":[19],"is":[20,30,66],"challenging":[21],"since":[22],"the":[23,47,57,61,64,69,74,92,97,103,107],"object":[24],"to":[25,152,162],"be":[26],"reconstructed":[27],"(the":[28],"heart)":[29],"continuously":[31],"changing":[32],"during":[33],"signal":[34,87],"acquisition.":[35],"In":[36],"this":[37,166],"paper,":[38],"we":[39],"propose":[40],"reconstruction":[42,133],"approach":[43,109,175],"based":[44],"on":[45,135],"representing":[46],"with":[50,68,80,137],"an":[51,85,158],"implicit":[52,159],"neural":[53,145],"network":[54,58,72],"and":[55,89,99,127,147],"fitting":[56],"so":[59],"that":[60,156],"representation":[62,160],"consistent":[67],"The":[71],"in":[73,95,116,191],"form":[75],"multi-layer":[78],"perceptron":[79],"Fourier-feature":[81],"inputs":[82],"acts":[83],"as":[84],"effective":[86],"prior":[88],"enables":[90],"adjusting":[91],"regularization":[93],"strength":[94],"both":[96],"spatial":[98],"temporal":[100],"dimensions":[101],"signal.":[104],"We":[105],"study":[106],"proposed":[108],"for":[110,121],"2D":[111],"free-breathing":[112],"cardiac":[113],"MRI":[115],"different":[117,122],"operating":[118],"regimes,":[119],"i.e.,":[120],"image":[123,149],"resolutions,":[124],"slice":[125],"thicknesses,":[126],"acquisition":[128],"lengths.":[129],"Our":[130,174],"method":[131,155],"achieves":[132],"quality":[134,150],"par":[136],"or":[138,183],"slightly":[139],"better":[140],"than":[141],"state-of-the-art":[142],"untrained":[143],"convolutional":[144],"networks":[146],"superior":[148],"compared":[151],"recent":[154],"fits":[157],"directly":[161],"k-space":[163],"However,":[165],"comes":[167],"at":[168],"relatively":[170],"high":[171],"computational":[172],"cost.":[173],"does":[176],"not":[177],"require":[178],"any":[179],"additional":[180],"patient":[181],"data":[182],"biosensors":[184],"including":[185],"electrocardiography,":[186],"making":[187],"it":[188],"potentially":[189],"applicable":[190],"wide":[193],"range":[194],"clinical":[196],"scenarios.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":36},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-07T14:30:12.667765","created_date":"2025-10-10T00:00:00"}
