{"id":"https://openalex.org/W4401202517","doi":"https://doi.org/10.48550/arxiv.2407.20108","title":"Classification, Regression and Segmentation directly from k-Space in Cardiac MRI","display_name":"Classification, Regression and Segmentation directly from k-Space in Cardiac MRI","publication_year":2024,"publication_date":"2024-07-29","ids":{"openalex":"https://openalex.org/W4401202517","doi":"https://doi.org/10.48550/arxiv.2407.20108"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2407.20108","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.20108","pdf_url":"https://arxiv.org/pdf/2407.20108","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":null},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2407.20108","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101653829","display_name":"Ruochen Li","orcid":"https://orcid.org/0009-0002-1131-5385"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Li, Ruochen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004278800","display_name":"Jiazhen Pan","orcid":"https://orcid.org/0000-0002-6305-8117"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pan, Jiazhen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010382904","display_name":"Youxiang Zhu","orcid":"https://orcid.org/0009-0000-7294-1596"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Youxiang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114201246","display_name":"Juncheng Ni","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ni, Juncheng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5006461848","display_name":"Daniel Rueckert","orcid":"https://orcid.org/0000-0002-5683-5889"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rueckert, Daniel","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101653829"],"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.8683000206947327,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.8683000206947327,"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/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.8191999793052673,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.8090999722480774,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6441212296485901},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.6234017014503479},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49849390983581543},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.43240368366241455},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3846687972545624},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3496461510658264},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27557462453842163},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.21058157086372375}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6441212296485901},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.6234017014503479},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49849390983581543},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.43240368366241455},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3846687972545624},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3496461510658264},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27557462453842163},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.21058157086372375},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2407.20108","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.20108","pdf_url":"https://arxiv.org/pdf/2407.20108","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":null},{"id":"doi:10.48550/arxiv.2407.20108","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2407.20108","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2407.20108","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.20108","pdf_url":"https://arxiv.org/pdf/2407.20108","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":null},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4379231730","https://openalex.org/W4389858081","https://openalex.org/W2501551404","https://openalex.org/W4385583601","https://openalex.org/W4298131179","https://openalex.org/W2113201962","https://openalex.org/W4395685956","https://openalex.org/W2799953226","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Cardiac":[0],"Magnetic":[1],"Resonance":[2],"Imaging":[3,20],"(CMR)":[4],"is":[5,40,153],"the":[6,76,100,151,158,163],"gold":[7],"standard":[8],"for":[9],"diagnosing":[10],"cardiovascular":[11],"diseases.":[12],"Clinical":[13],"diagnoses":[14],"predominantly":[15],"rely":[16],"on":[17],"magnitude-only":[18],"Digital":[19],"and":[21,42,46,89,114,125,168],"Communications":[22],"in":[23,105],"Medicine":[24],"(DICOM)":[25],"images,":[26],"omitting":[27],"crucial":[28],"phase":[29,47],"information":[30],"that":[31],"might":[32],"provide":[33],"additional":[34],"diagnostic":[35],"benefits.":[36],"In":[37,54],"contrast,":[38],"k-space":[39,67,152,167],"complex-valued":[41],"encompasses":[43],"both":[44],"magnitude":[45],"information,":[48],"while":[49],"humans":[50],"cannot":[51],"directly":[52],"perceive.":[53],"this":[55,96,109],"work,":[56],"we":[57],"propose":[58],"KMAE,":[59],"a":[60,131],"Transformer-based":[61],"model":[62,97,110,142],"specifically":[63],"designed":[64],"to":[65,75,98,118,161],"process":[66],"data":[68],"directly,":[69],"eliminating":[70],"conventional":[71],"intermediary":[72],"conversion":[73],"steps":[74],"image":[77],"domain.":[78],"KMAE":[79],"can":[80],"handle":[81],"critical":[82],"cardiac":[83,90,106],"disease":[84],"classification,":[85],"relevant":[86],"phenotype":[87],"regression,":[88],"morphology":[91],"segmentation":[92,128],"tasks.":[93],"We":[94,156],"utilize":[95],"investigate":[99],"potential":[101,165],"of":[102,135,166],"k-space-based":[103],"diagnosis":[104,172],"MRI.":[107],"Notably,":[108],"achieves":[111],"competitive":[112],"classification":[113],"regression":[115],"performance":[116,129,145],"compared":[117],"image-domain":[119],"methods":[120],"e.g.":[121],"Masked":[122],"Autoencoders":[123],"(MAEs)":[124],"delivers":[126],"satisfactory":[127],"with":[130,146,173],"myocardium":[132],"dice":[133],"score":[134],"0.884.":[136],"Last":[137],"but":[138],"not":[139],"least,":[140],"our":[141],"exhibits":[143],"robust":[144],"consistent":[147],"results":[148],"even":[149],"when":[150],"8*":[154],"undersampled.":[155],"encourage":[157],"MR":[159],"community":[160],"explore":[162],"untapped":[164],"pursue":[169],"end-to-end,":[170],"automated":[171],"reduced":[174],"human":[175],"intervention.":[176]},"counts_by_year":[],"updated_date":"2026-03-14T08:43:22.919905","created_date":"2025-10-10T00:00:00"}
