{"id":"https://openalex.org/W2398062891","doi":"https://doi.org/10.1007/978-3-319-24571-3_62","title":"Robust Transmural Electrophysiological Imaging: Integrating Sparse and Dynamic Physiological Models into ECG-Based Inference","display_name":"Robust Transmural Electrophysiological Imaging: Integrating Sparse and Dynamic Physiological Models into ECG-Based Inference","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2398062891","doi":"https://doi.org/10.1007/978-3-319-24571-3_62","mag":"2398062891"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-319-24571-3_62","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-319-24571-3_62","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-319-24571-3_62.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/978-3-319-24571-3_62.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5040565462","display_name":"Jingjia Xu","orcid":"https://orcid.org/0000-0003-0121-5954"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jingjia Xu","raw_affiliation_strings":["Rochester Institute of Technology, Rochester, NY, 14623, USA"],"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology, Rochester, NY, 14623, USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077573193","display_name":"John L. Sapp","orcid":"https://orcid.org/0000-0002-9602-2751"},"institutions":[{"id":"https://openalex.org/I129902397","display_name":"Dalhousie University","ror":"https://ror.org/01e6qks80","country_code":"CA","type":"education","lineage":["https://openalex.org/I129902397"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"John L. Sapp","raw_affiliation_strings":["Dalhousie Unviersity, Halifax, NS, Canada"],"affiliations":[{"raw_affiliation_string":"Dalhousie Unviersity, Halifax, NS, Canada","institution_ids":["https://openalex.org/I129902397"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070940718","display_name":"Azar Rahimi Dehaghani","orcid":null},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Azar Rahimi Dehaghani","raw_affiliation_strings":["Rochester Institute of Technology, Rochester, NY, 14623, USA"],"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology, Rochester, NY, 14623, USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101421765","display_name":"Fei Gao","orcid":"https://orcid.org/0000-0003-0300-6240"},"institutions":[{"id":"https://openalex.org/I4210151799","display_name":"Siemens Healthcare (United States)","ror":"https://ror.org/054962n91","country_code":"US","type":"company","lineage":["https://openalex.org/I4210151799"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fei Gao","raw_affiliation_strings":["Molecular Imaging Division, Siemens Medical Solutions, Knoxville, TN, 37932, USA"],"affiliations":[{"raw_affiliation_string":"Molecular Imaging Division, Siemens Medical Solutions, Knoxville, TN, 37932, USA","institution_ids":["https://openalex.org/I4210151799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010690465","display_name":"B. Milan Hor\u00e1\u010dek","orcid":"https://orcid.org/0000-0001-6902-7787"},"institutions":[{"id":"https://openalex.org/I129902397","display_name":"Dalhousie University","ror":"https://ror.org/01e6qks80","country_code":"CA","type":"education","lineage":["https://openalex.org/I129902397"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Milan Horacek","raw_affiliation_strings":["Dalhousie Unviersity, Halifax, NS, Canada"],"affiliations":[{"raw_affiliation_string":"Dalhousie Unviersity, Halifax, NS, Canada","institution_ids":["https://openalex.org/I129902397"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101710700","display_name":"Linwei Wang","orcid":"https://orcid.org/0000-0002-5678-2369"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Linwei Wang","raw_affiliation_strings":["Rochester Institute of Technology, Rochester, NY, 14623, USA"],"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology, Rochester, NY, 14623, USA","institution_ids":["https://openalex.org/I155173764"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5040565462"],"corresponding_institution_ids":["https://openalex.org/I155173764"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":{"value":5000,"currency":"EUR","value_usd":5392},"fwci":12.3014,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.98019802,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"519","last_page":"527"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10217","display_name":"Cardiac electrophysiology and arrhythmias","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/T10217","display_name":"Cardiac electrophysiology and arrhythmias","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/T11021","display_name":"ECG Monitoring and Analysis","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9965000152587891,"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/inference","display_name":"Inference","score":0.8536306023597717},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7608415484428406},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.6788796186447144},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5320879817008972},{"id":"https://openalex.org/keywords/cardiac-electrophysiology","display_name":"Cardiac electrophysiology","score":0.49794793128967285},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.42503297328948975},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.370535671710968},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36602699756622314},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.323574423789978},{"id":"https://openalex.org/keywords/electrophysiology","display_name":"Electrophysiology","score":0.3085952401161194},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.09591296315193176},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09334945678710938}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.8536306023597717},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7608415484428406},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.6788796186447144},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5320879817008972},{"id":"https://openalex.org/C61381695","wikidata":"https://www.wikidata.org/wiki/Q3302130","display_name":"Cardiac electrophysiology","level":3,"score":0.49794793128967285},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.42503297328948975},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.370535671710968},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36602699756622314},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.323574423789978},{"id":"https://openalex.org/C185263204","wikidata":"https://www.wikidata.org/wiki/Q1154774","display_name":"Electrophysiology","level":2,"score":0.3085952401161194},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.09591296315193176},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09334945678710938},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-319-24571-3_62","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-319-24571-3_62","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-319-24571-3_62.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.1007/978-3-319-24571-3_62","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-319-24571-3_62","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-319-24571-3_62.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5162784776","display_name":null,"funder_award_id":"ACI-1350374","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6671297155","display_name":null,"funder_award_id":"CAREER","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8368080021","display_name":"CAREER: Integrating Physical Models into Data-Driven Inference","funder_award_id":"1350374","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2398062891.pdf","grobid_xml":"https://content.openalex.org/works/W2398062891.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W575122527","https://openalex.org/W1492221128","https://openalex.org/W2012155513","https://openalex.org/W2021611778","https://openalex.org/W2046059930","https://openalex.org/W2061929769","https://openalex.org/W2103450980","https://openalex.org/W2109782778","https://openalex.org/W2145096794","https://openalex.org/W2147507822","https://openalex.org/W2241296611","https://openalex.org/W4205430442"],"related_works":["https://openalex.org/W2274750791","https://openalex.org/W3044098214","https://openalex.org/W1007316647","https://openalex.org/W203924752","https://openalex.org/W2055549109","https://openalex.org/W1968555577","https://openalex.org/W2748521320","https://openalex.org/W2006154469","https://openalex.org/W2047253462","https://openalex.org/W2119568772"],"abstract_inverted_index":{"Noninvasive":[0],"inference":[1,35,50,97,107,130],"of":[2,18,42,79,91,113,118,131,138,153,159],"patient-specific":[3,132],"intramural":[4,133],"electrical":[5,134,162],"activity":[6,163],"from":[7],"surface":[8],"electrocardiograms":[9],"(ECG)":[10],"lacks":[11],"a":[12,29,84],"unique":[13],"solution":[14,70,81],"in":[15,56,87,143],"the":[16,39,49,62,76,80,89,95,104,111,115,154,160],"absence":[17],"prior":[19],"assumptions.":[20],"While":[21],"3D":[22],"cardiac":[23,43,119],"electrophysiological":[24],"models":[25],"emerged":[26],"to":[27,51,54,71,164],"be":[28,52],"viable":[30],"vehicle":[31],"for":[32,48,127],"constraining":[33],"this":[34,72,139],"with":[36],"knowledge":[37],"about":[38],"spatiotemporal":[40,125],"dynamics":[41,126],"excitation,":[44],"it":[45],"is":[46,141],"important":[47],"robust":[53],"errors":[55],"these":[57],"high-dimensional":[58],"model":[59],"predictions":[60],"given":[61],"limited":[63],"ECG":[64],"data.":[65,168],"We":[66,102],"present":[67,103,151],"an":[68,128],"innovative":[69],"problem":[73],"by":[74,99],"exploiting":[75],"low-dimensional":[77],"structure":[78],"space":[82],"\u2013":[83,93],"powerful":[85],"regularizer":[86],"overcoming":[88],"lack":[90],"measurements":[92],"within":[94],"dynamic":[96],"guided":[98],"physiological":[100],"models.":[101],"first":[105,155],"Bayesian":[106],"framework":[108],"that":[109],"allows":[110],"exploration":[112],"both":[114,144],"spatial":[116],"sparsity":[117],"excitation":[120],"and":[121,146],"its":[122],"complex":[123],"nonlinear":[124],"improved":[129],"activity.":[135],"The":[136],"benefit":[137],"integration":[140],"verified":[142],"synthetic":[145],"real-data":[147],"experiments,":[148],"where":[149],"we":[150],"one":[152],"detailed,":[156],"point-by-point":[157],"comparison":[158],"reconstructed":[161],"in-vivo":[165],"catheter":[166],"mapping":[167]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":2}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}