{"id":"https://openalex.org/W4296594553","doi":"https://doi.org/10.48550/arxiv.2209.09678","title":"Detecting respiratory motion artefacts for cardiovascular MRIs to ensure high-quality segmentation","display_name":"Detecting respiratory motion artefacts for cardiovascular MRIs to ensure high-quality segmentation","publication_year":2022,"publication_date":"2022-09-20","ids":{"openalex":"https://openalex.org/W4296594553","doi":"https://doi.org/10.48550/arxiv.2209.09678"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2209.09678","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2209.09678","pdf_url":"https://arxiv.org/pdf/2209.09678","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":null,"license_id":null,"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/2209.09678","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023229664","display_name":"Amin Ranem","orcid":"https://orcid.org/0000-0003-0783-6903"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ranem, Amin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035217207","display_name":"John Kalkhof","orcid":"https://orcid.org/0000-0001-7316-1903"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kalkhof, John","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010602607","display_name":"Caner \u00d6zer","orcid":"https://orcid.org/0000-0001-9044-143X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"\u00d6zer, Caner","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016363044","display_name":"Anirban Mukhopadhyay","orcid":"https://orcid.org/0000-0001-8128-3521"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mukhopadhyay, Anirban","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5080738214","display_name":"\u0130lkay \u00d6ks\u00fcz","orcid":"https://orcid.org/0000-0001-6478-0534"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Oksuz, Ilkay","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"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":0.9994999766349792,"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":0.9994999766349792,"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":0.9994000196456909,"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/workflow","display_name":"Workflow","score":0.6643648743629456},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6553980112075806},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6405688524246216},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6307601928710938},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5262522101402283},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5262039303779602},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42684459686279297},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.39677876234054565},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.1183408796787262}],"concepts":[{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.6643648743629456},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6553980112075806},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6405688524246216},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6307601928710938},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5262522101402283},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5262039303779602},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42684459686279297},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39677876234054565},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.1183408796787262},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2209.09678","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2209.09678","pdf_url":"https://arxiv.org/pdf/2209.09678","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2209.09678","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2209.09678","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:2209.09678","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2209.09678","pdf_url":"https://arxiv.org/pdf/2209.09678","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"score":0.41999998688697815,"id":"https://metadata.un.org/sdg/1","display_name":"No poverty"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1981780420","https://openalex.org/W2182707996","https://openalex.org/W45233828","https://openalex.org/W2964988449","https://openalex.org/W2397952901","https://openalex.org/W2029380707","https://openalex.org/W4255934811","https://openalex.org/W2465382974","https://openalex.org/W2010229520","https://openalex.org/W4388446985"],"abstract_inverted_index":{"While":[0],"machine":[1],"learning":[2],"approaches":[3],"perform":[4],"well":[5],"on":[6,73],"their":[7,150],"training":[8],"domain,":[9],"they":[10],"generally":[11],"tend":[12],"to":[13,69,105,158],"fail":[14],"in":[15,31,55,92,132,149],"a":[16,28,45,49,106,155],"real-world":[17],"application.":[18],"In":[19],"cardiovascular":[20,167],"magnetic":[21],"resonance":[22],"imaging":[23],"(CMR),":[24],"respiratory":[25,53],"motion":[26,54,136],"represents":[27],"major":[29],"challenge":[30,60],"terms":[32],"of":[33,134],"acquisition":[34],"quality":[35,76,108,161],"and":[36,40,129,147,163],"therefore":[37],"subsequent":[38],"analysis":[39],"final":[41],"diagnosis.":[42,116],"We":[43],"present":[44],"workflow":[46],"which":[47],"predicts":[48],"severity":[50],"score":[51],"for":[52,57,67,114,123,166],"CMR":[56,75,102],"the":[58,74,87,93,100],"CMRxMotion":[59],"2022.":[61],"This":[62],"is":[63,89,112,172],"an":[64,120],"important":[65],"tool":[66],"technicians":[68,148],"immediately":[70],"provide":[71],"feedback":[72],"during":[77],"acquisition,":[78],"as":[79],"poor-quality":[80],"images":[81],"can":[82,144],"directly":[83],"be":[84],"re-acquired":[85],"while":[86],"patient":[88],"still":[90],"available":[91,173],"vicinity.":[94],"Thus,":[95],"our":[96,140],"method":[97],"ensures":[98],"that":[99],"acquired":[101],"holds":[103],"up":[104],"specific":[107],"standard":[109],"before":[110],"it":[111,118],"used":[113],"further":[115],"Therefore,":[117],"enables":[119],"efficient":[121],"base":[122,171],"proper":[124,160],"diagnosis":[125],"without":[126],"having":[127],"time":[128],"cost-intensive":[130],"re-acquisitions":[131],"cases":[133],"severe":[135],"artefacts.":[137],"Combined":[138],"with":[139],"segmentation":[141],"model,":[142],"this":[143],"help":[145],"cardiologists":[146],"daily":[151],"routine":[152],"by":[153],"providing":[154],"complete":[156],"pipeline":[157],"guarantee":[159],"assessment":[162],"genuine":[164],"segmentations":[165],"scans.":[168],"The":[169],"code":[170],"at":[174],"https://github.com/MECLabTUDA/QA_med_data/tree/dev_QA_CMRxMotion.":[175]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}