{"id":"https://openalex.org/W4393027448","doi":"https://doi.org/10.48550/arxiv.2403.12611","title":"MOCCA: A Fast Algorithm for Parallel MRI Reconstruction Using Model Based Coil Calibration","display_name":"MOCCA: A Fast Algorithm for Parallel MRI Reconstruction Using Model Based Coil Calibration","publication_year":2024,"publication_date":"2024-03-19","ids":{"openalex":"https://openalex.org/W4393027448","doi":"https://doi.org/10.48550/arxiv.2403.12611"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2403.12611","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2403.12611","pdf_url":"https://arxiv.org/pdf/2403.12611","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2403.12611","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059739223","display_name":"Gerlind Plonka","orcid":"https://orcid.org/0000-0002-3232-0573"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Plonka, Gerlind","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5079647594","display_name":"Yannick Riebe","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Riebe, Yannick","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5059739223"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"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":0.9975000023841858,"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":0.9975000023841858,"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":0.9908999800682068,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9717000126838684,"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/calibration","display_name":"Calibration","score":0.7257243394851685},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6348230242729187},{"id":"https://openalex.org/keywords/electromagnetic-coil","display_name":"Electromagnetic coil","score":0.5169293284416199},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.49395447969436646},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.32994094491004944},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.32746201753616333},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18412944674491882},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11159977316856384},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.08795243501663208}],"concepts":[{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.7257243394851685},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6348230242729187},{"id":"https://openalex.org/C30403606","wikidata":"https://www.wikidata.org/wiki/Q2981904","display_name":"Electromagnetic coil","level":2,"score":0.5169293284416199},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.49395447969436646},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.32994094491004944},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.32746201753616333},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18412944674491882},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11159977316856384},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.08795243501663208},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2403.12611","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2403.12611","pdf_url":"https://arxiv.org/pdf/2403.12611","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2403.12611","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2403.12611","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2403.12611","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2403.12611","pdf_url":"https://arxiv.org/pdf/2403.12611","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4644177491","display_name":"EXPOnential analysis emPOWERing innovation","funder_award_id":"101008231","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G5789947139","display_name":null,"funder_award_id":"CRC 1456","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G7633418676","display_name":null,"funder_award_id":"RTG 2088","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4393027448.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2387913980","https://openalex.org/W1975610155","https://openalex.org/W2053286651","https://openalex.org/W2181743346","https://openalex.org/W3100052852","https://openalex.org/W4237158276","https://openalex.org/W2187401768","https://openalex.org/W4364321570"],"abstract_inverted_index":{"We":[0,74],"propose":[1],"a":[2,30,76,98],"new":[3],"fast":[4],"algorithm":[5,47],"for":[6,33,57,70],"simultaneous":[7],"recovery":[8],"of":[9,14,41,52,80],"the":[10,15,34,81,107],"coil":[11,35],"sensitivities":[12,36],"and":[13,62,65],"magnetization":[16],"image":[17],"from":[18],"incomplete":[19,71],"Fourier":[20],"measurements":[21],"in":[22],"parallel":[23],"MRI.":[24],"Our":[25,111],"approach":[26],"is":[27,104],"based":[28],"on":[29],"parameter":[31,109],"model":[32],"using":[37],"bivariate":[38],"trigonometric":[39],"polynomials":[40],"small":[42],"degree.":[43],"The":[44],"derived":[45],"MOCCA":[46,89,116],"has":[48],"low":[49],"computational":[50],"complexity":[51],"$O(N_c":[53],"N^2":[54],"\\log":[55],"N)$":[56],"$N":[58],"\\times":[59],"N$":[60],"images":[61],"$N_c$":[63],"coils":[64],"achieves":[66,90],"very":[67],"good":[68,92],"performance":[69],"MRI":[72],"data.":[73],"present":[75],"complete":[77],"mathematical":[78],"analysis":[79],"proposed":[82],"reconstruction":[83,93,121],"method.":[84],"Further,":[85],"we":[86],"show":[87,114],"that":[88,115],"similarly":[91],"results":[94],"as":[95],"ESPIRiT":[96],"with":[97],"considerably":[99],"smaller":[100],"numerical":[101,112],"effort":[102],"which":[103],"due":[105],"to":[106],"employed":[108],"model.":[110],"examples":[113],"can":[117],"outperform":[118],"several":[119],"other":[120],"methods.":[122]},"counts_by_year":[],"updated_date":"2026-05-21T09:19:25.381259","created_date":"2025-10-10T00:00:00"}