{"id":"https://openalex.org/W3017185992","doi":null,"title":"An Adaptive Intelligence Algorithm for Undersampled Knee MRI Reconstruction: Application to the 2019 fastMRI Challenge","display_name":"An Adaptive Intelligence Algorithm for Undersampled Knee MRI Reconstruction: Application to the 2019 fastMRI Challenge","publication_year":2020,"publication_date":"2020-04-15","ids":{"openalex":"https://openalex.org/W3017185992","mag":"3017185992"},"language":"en","primary_location":{"id":"mag:3017185992","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2004.07339","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2004.07339","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034214530","display_name":"Nicola Pezzotti","orcid":"https://orcid.org/0000-0001-9554-4331","observed_orcids":["https://orcid.org/0000-0001-9554-4331","https://orcid.org/0000-0001-7346-9182"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nicola Pezzotti","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-9554-4331","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061429872","display_name":"Sahar Yousefi","orcid":"https://orcid.org/0000-0003-2396-2504","observed_orcids":["https://orcid.org/0000-0003-2396-2504","https://orcid.org/0000-0001-9425-4543"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sahar Yousefi","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-2396-2504","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049164680","display_name":"Mohamed S. Elmahdy","orcid":"https://orcid.org/0000-0001-8432-3082","observed_orcids":["https://orcid.org/0000-0001-8432-3082"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mohamed S. Elmahdy","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-8432-3082","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044645819","display_name":"Jeroen Hendrikus Fransiscus Van Gemert","orcid":"https://orcid.org/0000-0002-2692-9286","observed_orcids":["https://orcid.org/0000-0002-2692-9286"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jeroen Hendrikus Fransiscus Van Gemert","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042360820","display_name":"Christophe Sch\u00fclke","orcid":"https://orcid.org/0000-0002-9122-7862","observed_orcids":["https://orcid.org/0000-0002-9122-7862"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Christophe Sch\u00fclke","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086133730","display_name":"Mariya Doneva","orcid":"https://orcid.org/0000-0003-0292-5069","observed_orcids":["https://orcid.org/0000-0003-0292-5069"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mariya Doneva","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-0292-5069","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031476041","display_name":"Tim Tolker\u2010Nielsen","orcid":"https://orcid.org/0000-0002-9751-474X","observed_orcids":["https://orcid.org/0000-0002-9751-474X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tim Tolker\u2010Nielsen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003745304","display_name":"Sergey Kastryulin","orcid":"https://orcid.org/0000-0002-9381-0541","observed_orcids":["https://orcid.org/0000-0002-9381-0541"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sergey Kastryulin","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-9381-0541","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019003563","display_name":"Boudewijn P. F. Lelieveldt","orcid":"https://orcid.org/0000-0001-8269-7603","observed_orcids":["https://orcid.org/0000-0001-8269-7603"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Boudewijn P. F. Lelieveldt","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-8269-7603","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064910180","display_name":"Matthias J.P. van Osch","orcid":"https://orcid.org/0000-0001-7034-8959","observed_orcids":["https://orcid.org/0000-0001-7034-8959"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Matthias J.P. van Osch","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-7034-8959","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016458559","display_name":"Elwin de Weerdt","orcid":"https://orcid.org/0000-0001-8199-4737","observed_orcids":["https://orcid.org/0000-0001-8199-4737"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Elwin de Weerdt","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-8199-4737","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5025788902","display_name":"Marius Staring","orcid":"https://orcid.org/0000-0003-2885-5812","observed_orcids":["https://orcid.org/0000-0003-2885-5812"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marius Staring","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-2885-5812","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9955999851226807,"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":0.9955999851226807,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.000699999975040555,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.00039999998989515007,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/adaptive-intelligence","display_name":"adaptive intelligence","score":0.890999972820282},{"id":"https://openalex.org/keywords/knee-mri","display_name":"knee MRI","score":0.6600000262260437},{"id":"https://openalex.org/keywords/k-space-undersampling","display_name":"k-space undersampling","score":0.8009999990463257},{"id":"https://openalex.org/keywords/mri-reconstruction","display_name":"MRI reconstruction","score":0.6650000214576721},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"compressed sensing","score":0.7649999856948853},{"id":"https://openalex.org/keywords/deep-neural-network","display_name":"deep neural network","score":0.8019999861717224},{"id":"https://openalex.org/keywords/multi-coil-mri","display_name":"multi-coil MRI","score":0.7860000133514404},{"id":"https://openalex.org/keywords/accelerated-mri-acquisition","display_name":"accelerated MRI acquisition","score":0.6690000295639038}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7612171173095703},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.6174540519714355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6010768413543701},{"id":"https://openalex.org/C30403606","wikidata":"https://www.wikidata.org/wiki/Q2981904","display_name":"Electromagnetic coil","level":2,"score":0.5322980880737305},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5190846920013428},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.47214487195014954},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4687870740890503},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.44594892859458923},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4410085082054138},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4364827275276184},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4216960072517395},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33679163455963135},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.321756511926651},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2019258439540863},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11403131484985352},{"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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:3017185992","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2004.07339","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null}],"best_oa_location":{"id":"mag:3017185992","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2004.07339","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1580389772","https://openalex.org/W1812490466","https://openalex.org/W1901129140","https://openalex.org/W1972089774","https://openalex.org/W2082029531","https://openalex.org/W2092663520","https://openalex.org/W2100556411","https://openalex.org/W2101675075","https://openalex.org/W2103955025","https://openalex.org/W2117882039","https://openalex.org/W2133665775","https://openalex.org/W2163973643","https://openalex.org/W2167233877","https://openalex.org/W2296616510","https://openalex.org/W2331128040","https://openalex.org/W2552808051","https://openalex.org/W2562637781","https://openalex.org/W2611467245","https://openalex.org/W2738743584","https://openalex.org/W2773850766","https://openalex.org/W2791621240","https://openalex.org/W2796177458","https://openalex.org/W2798559986","https://openalex.org/W2803224943","https://openalex.org/W2883105305","https://openalex.org/W2883718552","https://openalex.org/W2900756484","https://openalex.org/W2950936580","https://openalex.org/W2963074624","https://openalex.org/W2964121744","https://openalex.org/W2970578216","https://openalex.org/W2970803838","https://openalex.org/W2972417789","https://openalex.org/W2973306787","https://openalex.org/W2980869080","https://openalex.org/W2994689640","https://openalex.org/W2998322489","https://openalex.org/W2999511788","https://openalex.org/W2999819348","https://openalex.org/W3001319253","https://openalex.org/W3003650457","https://openalex.org/W3091916112"],"related_works":["https://openalex.org/W3096785819","https://openalex.org/W2998322489","https://openalex.org/W3211349725","https://openalex.org/W4396215557","https://openalex.org/W2979703761","https://openalex.org/W3160162492","https://openalex.org/W4415252617","https://openalex.org/W4296057813","https://openalex.org/W4392909351","https://openalex.org/W4283032593"],"abstract_inverted_index":{"Adaptive":[0],"intelligence":[1,24],"aims":[2],"at":[3],"empowering":[4],"machine":[5],"learning":[6],"techniques":[7],"with":[8,102],"the":[9,20,48,63,78,94,108,120,137,141,145,151,158],"additional":[10],"use":[11],"of":[12,22,157],"domain":[13],"knowledge.":[14],"In":[15],"this":[16],"work,":[17],"we":[18],"present":[19],"application":[21],"adaptive":[23],"to":[25,46,55,93],"accelerate":[26],"MR":[27],"acquisition.":[28],"Starting":[29],"from":[30,77],"undersampled":[31],"k-space":[32],"data,":[33],"an":[34,124],"iterative":[35],"learning-based":[36],"reconstruction":[37,60],"scheme":[38],"inspired":[39],"by":[40,83,119],"compressed":[41],"sensing":[42],"theory":[43],"is":[44],"used":[45],"reconstruct":[47],"images.":[49],"We":[50],"adopt":[51],"deep":[52],"neural":[53],"networks":[54],"refine":[56],"and":[57,70,87,133,144,154],"correct":[58],"prior":[59],"assumptions":[61],"given":[62],"training":[64],"data.":[65],"The":[66],"network":[67],"was":[68,117],"trained":[69],"tested":[71],"on":[72,100,123,135],"a":[73,103],"knee":[74],"MRI":[75],"dataset":[76],"2019":[79],"fastMRI":[80,121],"challenge":[81,95,126],"organized":[82],"Facebook":[84],"AI":[85],"Research":[86],"NYU":[88],"Langone":[89],"Health.":[90],"All":[91],"submissions":[92,111],"were":[96,112],"initially":[97],"ranked":[98,129],"based":[99],"similarity":[101],"known":[104],"groundtruth,":[105],"after":[106],"which":[107],"top":[109],"4":[110],"evaluated":[113,118],"radiologically.":[114],"Our":[115],"method":[116],"organizers":[122],"independent":[125],"dataset.":[127],"It":[128],"#1,":[130,132],"shared":[131],"#3":[134],"respectively":[136],"8x":[138],"accelerated":[139],"multi-coil,":[140,143],"4x":[142,146],"single-coil":[147],"track.":[148],"This":[149],"demonstrates":[150],"superior":[152],"performance":[153],"wide":[155],"applicability":[156],"method.":[159]},"counts_by_year":[{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":4}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2020-04-24T00:00:00"}
