{"id":"https://openalex.org/W2983868340","doi":"https://doi.org/10.48550/arxiv.1911.02407","title":"Doppler Spectrum Classification with CNNs via Heatmap Location Encoding and a Multi-head Output Layer","display_name":"Doppler Spectrum Classification with CNNs via Heatmap Location Encoding and a Multi-head Output Layer","publication_year":2019,"publication_date":"2019-11-06","ids":{"openalex":"https://openalex.org/W2983868340","doi":"https://doi.org/10.48550/arxiv.1911.02407","mag":"2983868340"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:1911.02407","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1911.02407","pdf_url":"https://arxiv.org/pdf/1911.02407","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":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1911.02407","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Gilbert, Andrew","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gilbert, Andrew","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101719544","display_name":"Marit Holden","orcid":"https://orcid.org/0000-0003-0074-0829","observed_orcids":["https://orcid.org/0000-0003-0074-0829"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Holden, Marit","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012404498","display_name":"Line Eikvil","orcid":"https://orcid.org/0009-0006-9758-5747","observed_orcids":["https://orcid.org/0009-0006-9758-5747"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eikvil, Line","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079173064","display_name":"Mariia Rakhmail","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rakhmail, Mariia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101601779","display_name":"Aleksandar Babi\u0107","orcid":"https://orcid.org/0000-0001-7677-2451","observed_orcids":["https://orcid.org/0000-0001-7677-2451"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Babic, Aleksandar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030320671","display_name":"Svein Arne Aase","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aase, Svein Arne","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082938227","display_name":"Eigil Samset","orcid":"https://orcid.org/0000-0002-2755-2265","observed_orcids":["https://orcid.org/0000-0002-2755-2265"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Samset, Eigil","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5017717812","display_name":"Kristin McLeod","orcid":"https://orcid.org/0000-0002-2469-7039","observed_orcids":["https://orcid.org/0000-0002-2469-7039"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"McLeod, Kristin","raw_affiliation_strings":[],"raw_orcid":null,"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":2,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.35989999771118164,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.35989999771118164,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.15469999611377716,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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":0.11500000208616257,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/echocardiography","display_name":"echocardiography","score":0.7770000100135803},{"id":"https://openalex.org/keywords/automatic-measurement","display_name":"automated measurement","score":0.35899999737739563},{"id":"https://openalex.org/keywords/confidence-measures","display_name":"confidence measures","score":0.8980000019073486},{"id":"https://openalex.org/keywords/resource-limited-environments","display_name":"resource-constrained environments","score":0.7129999995231628},{"id":"https://openalex.org/keywords/cardiac-blood-flow","display_name":"cardiac blood flow","score":0.45899999141693115},{"id":"https://openalex.org/keywords/myocardial-wall-motion","display_name":"myocardial wall motion","score":0.9010000228881836}],"concepts":[{"id":"https://openalex.org/C2780312720","wikidata":"https://www.wikidata.org/wiki/Q5689100","display_name":"Head (geology)","level":2,"score":0.7246996164321899},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.6812572479248047},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.5875564813613892},{"id":"https://openalex.org/C142757262","wikidata":"https://www.wikidata.org/wiki/Q76436","display_name":"Doppler effect","level":2,"score":0.5525734424591064},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5483159422874451},{"id":"https://openalex.org/C156778621","wikidata":"https://www.wikidata.org/wiki/Q1365748","display_name":"Spectrum (functional analysis)","level":2,"score":0.5279585123062134},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38550862669944763},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.340725302696228},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.33162981271743774},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.23260605335235596},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.1367810070514679},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.129957914352417},{"id":"https://openalex.org/C171250308","wikidata":"https://www.wikidata.org/wiki/Q11468","display_name":"Nanotechnology","level":1,"score":0.055662691593170166},{"id":"https://openalex.org/C114793014","wikidata":"https://www.wikidata.org/wiki/Q52109","display_name":"Geomorphology","level":1,"score":0.0},{"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/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:1911.02407","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1911.02407","pdf_url":"https://arxiv.org/pdf/1911.02407","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":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.1911.02407","doi":"https://doi.org/10.48550/arxiv.1911.02407","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1911.02407","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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1911.02407","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1911.02407","pdf_url":"https://arxiv.org/pdf/1911.02407","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":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.504800021648407,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W18219543","https://openalex.org/W582134693","https://openalex.org/W2012942264","https://openalex.org/W2037916763","https://openalex.org/W2081100433","https://openalex.org/W2184188583","https://openalex.org/W2194775991","https://openalex.org/W2624871570","https://openalex.org/W2626967530","https://openalex.org/W2784710428","https://openalex.org/W2894839648","https://openalex.org/W2900555488","https://openalex.org/W2963428668","https://openalex.org/W3123318516","https://openalex.org/W4394670654"],"related_works":["https://openalex.org/W3097502728","https://openalex.org/W4235381733","https://openalex.org/W2113206756","https://openalex.org/W2355022049","https://openalex.org/W2060429446","https://openalex.org/W2741782512","https://openalex.org/W3011302839","https://openalex.org/W2371035601","https://openalex.org/W2392958391","https://openalex.org/W3155227409"],"abstract_inverted_index":{"Spectral":[0],"Doppler":[1,85,99,209],"measurements":[2,13,34],"are":[3],"an":[4],"important":[5,15],"part":[6],"of":[7,32,46,152,162],"the":[8,44,47,58,93,127,144,147,153,192],"standard":[9],"echocardiographic":[10],"examination.":[11],"These":[12],"give":[14],"insight":[16],"into":[17,87],"myocardial":[18],"motion":[19],"and":[20,111,131,200],"blood":[21],"flow":[22],"providing":[23],"clinicians":[24],"with":[25,40,120],"parameters":[26],"for":[27,134,197],"diagnostic":[28,48],"decision":[29],"making.":[30],"Many":[31],"these":[33],"can":[35,101,171],"currently":[36],"be":[37,66,102],"performed":[38,67],"automatically":[39,82],"high":[41],"accuracy,":[42],"increasing":[43],"efficiency":[45],"pipeline.":[49],"However,":[50],"full":[51],"automation":[52],"is":[53,195],"not":[54],"yet":[55],"available":[56],"because":[57],"user":[59],"must":[60],"manually":[61],"select":[62],"which":[63],"measurement":[64,88],"should":[65],"on":[68,180],"each":[69,97],"image.":[70],"In":[71],"this":[72],"work":[73],"we":[74,118,138],"develop":[75],"a":[76,105,140,181,186,202],"convolutional":[77],"neural":[78],"network":[79,123],"(CNN)":[80],"to":[81,113,125,166,208],"classify":[83],"cardiac":[84],"spectra":[86],"classes.":[89],"We":[90,155],"show":[91,167],"how":[92],"multi-modal":[94],"information":[95],"in":[96,146],"spectral":[98],"recording":[100],"combined":[103],"using":[104,143],"meta":[106],"parameter":[107],"post-processing":[108],"mapping":[109],"scheme":[110],"heatmaps":[112],"encode":[114],"coordinate":[115],"locations.":[116],"Additionally,":[117],"experiment":[119],"several":[121],"state-of-the-art":[122],"architectures":[124],"examine":[126],"tradeoff":[128],"between":[129],"accuracy":[130,179],"memory":[132],"usage":[133],"resource-constrained":[135],"environments.":[136],"Finally,":[137],"propose":[139],"confidence":[141,169],"metric":[142,170],"values":[145],"last":[148],"fully":[149,203],"connected":[150],"layer":[151],"network.":[154],"analyze":[156],"example":[157],"images":[158],"that":[159,191],"fall":[160],"outside":[161],"our":[163,168],"proposed":[164,193],"classes":[165],"prevent":[172],"many":[173],"misclassifications.":[174],"Our":[175],"algorithm":[176],"achieves":[177],"96%":[178],"test":[182],"set":[183],"drawn":[184],"from":[185,206],"separate":[187],"clinical":[188,198],"site,":[189],"indicating":[190],"method":[194],"suitable":[196],"adoption":[199],"enabling":[201],"automatic":[204],"pipeline":[205],"acquisition":[207],"spectrum":[210],"measurements.":[211]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2025-10-10T00:00:00"}
