{"id":"https://openalex.org/W3165493161","doi":"https://doi.org/10.1109/isbi48211.2021.9434134","title":"Deep Learning in Signal Linearization for Harmonic Imaging Application","display_name":"Deep Learning in Signal Linearization for Harmonic Imaging Application","publication_year":2021,"publication_date":"2021-04-13","ids":{"openalex":"https://openalex.org/W3165493161","doi":"https://doi.org/10.1109/isbi48211.2021.9434134","mag":"3165493161"},"language":"en","primary_location":{"id":"doi:10.1109/isbi48211.2021.9434134","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi48211.2021.9434134","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028542863","display_name":"Mariam Fouad","orcid":"https://orcid.org/0000-0003-2017-7690"},"institutions":[{"id":"https://openalex.org/I904495901","display_name":"Ruhr University Bochum","ror":"https://ror.org/04tsk2644","country_code":"DE","type":"education","lineage":["https://openalex.org/I904495901"]},{"id":"https://openalex.org/I96823368","display_name":"German University in Cairo","ror":"https://ror.org/03rjt0z37","country_code":"EG","type":"education","lineage":["https://openalex.org/I96823368"]}],"countries":["DE","EG"],"is_corresponding":true,"raw_author_name":"Mariam Fouad","raw_affiliation_strings":["German University in Cairo, Cairo, Egypt","Ruhr University Bochum, Bochum, Germany"],"affiliations":[{"raw_affiliation_string":"German University in Cairo, Cairo, Egypt","institution_ids":["https://openalex.org/I96823368"]},{"raw_affiliation_string":"Ruhr University Bochum, Bochum, Germany","institution_ids":["https://openalex.org/I904495901"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023997583","display_name":"Georg Schmitz","orcid":"https://orcid.org/0000-0001-5876-7202"},"institutions":[{"id":"https://openalex.org/I904495901","display_name":"Ruhr University Bochum","ror":"https://ror.org/04tsk2644","country_code":"DE","type":"education","lineage":["https://openalex.org/I904495901"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Georg Schmitz","raw_affiliation_strings":["Ruhr University Bochum, Bochum, Germany"],"affiliations":[{"raw_affiliation_string":"Ruhr University Bochum, Bochum, Germany","institution_ids":["https://openalex.org/I904495901"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114422898","display_name":"M. Huebner","orcid":"https://orcid.org/0000-0002-1162-8763"},"institutions":[{"id":"https://openalex.org/I51783024","display_name":"Brandenburg University of Technology Cottbus-Senftenberg","ror":"https://ror.org/02wxx3e24","country_code":"DE","type":"education","lineage":["https://openalex.org/I51783024"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Michael Huebner","raw_affiliation_strings":["BTU Cottbus - Senftenberg, Germany"],"affiliations":[{"raw_affiliation_string":"BTU Cottbus - Senftenberg, Germany","institution_ids":["https://openalex.org/I51783024"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039330377","display_name":"Mohamed A. Abd El Ghany","orcid":"https://orcid.org/0000-0002-6282-7738"},"institutions":[{"id":"https://openalex.org/I31512782","display_name":"Technical University of Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]},{"id":"https://openalex.org/I96823368","display_name":"German University in Cairo","ror":"https://ror.org/03rjt0z37","country_code":"EG","type":"education","lineage":["https://openalex.org/I96823368"]}],"countries":["DE","EG"],"is_corresponding":false,"raw_author_name":"Mohamed A. Abd El Ghany","raw_affiliation_strings":["German University in Cairo, Cairo, Egypt","Integrated Electronic Systems Lab, TU Darmstadt, Germany"],"affiliations":[{"raw_affiliation_string":"German University in Cairo, Cairo, Egypt","institution_ids":["https://openalex.org/I96823368"]},{"raw_affiliation_string":"Integrated Electronic Systems Lab, TU Darmstadt, Germany","institution_ids":["https://openalex.org/I31512782"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5028542863"],"corresponding_institution_ids":["https://openalex.org/I904495901","https://openalex.org/I96823368"],"apc_list":null,"apc_paid":null,"fwci":0.3843,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.59643791,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"957","last_page":"960"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9994000196456909,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9994000196456909,"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/T10662","display_name":"Ultrasonics and Acoustic Wave Propagation","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11698","display_name":"Underwater Acoustics Research","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/linearization","display_name":"Linearization","score":0.6267075538635254},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5915223360061646},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5534235239028931},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5142778754234314},{"id":"https://openalex.org/keywords/harmonic","display_name":"Harmonic","score":0.47906050086021423},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46448594331741333},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.42349669337272644},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.19189268350601196},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.14497095346450806},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.12176966667175293},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10897490382194519}],"concepts":[{"id":"https://openalex.org/C11210021","wikidata":"https://www.wikidata.org/wiki/Q1520713","display_name":"Linearization","level":3,"score":0.6267075538635254},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5915223360061646},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5534235239028931},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5142778754234314},{"id":"https://openalex.org/C127934551","wikidata":"https://www.wikidata.org/wiki/Q1148098","display_name":"Harmonic","level":2,"score":0.47906050086021423},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46448594331741333},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.42349669337272644},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.19189268350601196},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.14497095346450806},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.12176966667175293},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10897490382194519},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi48211.2021.9434134","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi48211.2021.9434134","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W10501323","https://openalex.org/W1522301498","https://openalex.org/W1677182931","https://openalex.org/W2017520353","https://openalex.org/W2159269332","https://openalex.org/W2174358748","https://openalex.org/W2516458981","https://openalex.org/W2885749203","https://openalex.org/W2890454219","https://openalex.org/W2893220000","https://openalex.org/W2906816906","https://openalex.org/W2938077033","https://openalex.org/W2963713691","https://openalex.org/W2974811400","https://openalex.org/W6631190155","https://openalex.org/W6754885506"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2553468687","https://openalex.org/W2611989081","https://openalex.org/W2953137247","https://openalex.org/W2731899572","https://openalex.org/W4230611425","https://openalex.org/W4294635752","https://openalex.org/W4304166257","https://openalex.org/W2362574016","https://openalex.org/W2666785071"],"abstract_inverted_index":{"Harmonic":[0,181],"imaging\u2019s":[1],"popularity":[2],"arises":[3],"from":[4,66,222],"its":[5,14],"ability":[6],"to":[7,59,193,227,256,274],"produce":[8],"high":[9],"contrast":[10],"resolution":[11],"images.":[12],"However,":[13],"need":[15],"for":[16,26,37,264],"at":[17],"least":[18],"two":[19],"successive":[20],"firings":[21],"remains":[22],"a":[23,27,34,43,57,67,108,125,128,134,152,253,271],"hindering":[24],"factor":[25],"faster":[28],"imaging":[29,41,215,234,269],"process.":[30],"In":[31],"this":[32],"work,":[33],"novel":[35],"approach":[36,235],"ultrasound":[38],"tissue":[39,122],"harmonic":[40,214,233,255,268],"using":[42],"single":[44],"firing":[45],"is":[46,53,116,190,211],"introduced":[47],"utilizing":[48],"deep":[49],"learning":[50],"concepts.":[51],"This":[52,232],"achieved":[54,151,236,250],"by":[55,205,216],"implementing":[56],"network":[58],"predict":[60],"the":[61,120,142,165,169,175,179,186,196,208,218,223,229,243,262,265,275],"linear":[62,126,170,220],"signal":[63,71],"component":[64,221],"output":[65],"received":[68,224],"nonlinear":[69,129,197,225],"echo":[70,226],"as":[72],"input.":[73],"Two":[74],"different":[75],"architectures":[76],"were":[77,147],"implemented:":[78],"Convolutional":[79],"AutoEncoder":[80],"(CAE)":[81],"and":[82,103,127,141,174,284],"U-Net":[83],"-":[84],"like":[85],"architecture.":[86],"The":[87,149],"dataset":[88],"consists":[89],"of":[90,96,105,137,158,240,267],"6k":[91],"3D":[92],"focused":[93],"K-wave":[94],"simulations":[95],"multi":[97],"scatterers":[98],"varying":[99],"in":[100,107,124,185,195,202,213],"position,":[101],"radius":[102],"speed":[104],"sound":[106],"tissue-like":[109],"medium":[110],"with":[111,119,270,280],"speckle":[112],"noise.":[113],"Each":[114],"simulation":[115],"performed":[117],"twice":[118],"same":[121],"properties":[123],"environment.":[130],"For":[131],"each":[132],"transmission,":[133],"transmission":[135],"frequency":[136],"7.5MHz":[138],"was":[139],"used":[140],"acquired":[143],"raw":[144],"RF":[145],"signals":[146,173],"sampled.":[148],"networks":[150],"Mean":[153],"Squared":[154],"Error":[155],"(MSE)":[156],"value":[157,184],"9.1x10":[159],"<sup":[160],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[161],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">-06</sup>":[162],",":[163],"on":[164],"validation":[166],"set":[167],"between":[168],"ground":[171],"truth":[172],"predicted":[176,188,219],"output.":[177],"Moreover,":[178],"Total":[180],"Distortion":[182],"(THD)":[183],"model\u2019s":[187],"results":[189,260],"1.615%":[191],"compared":[192],"31.75%":[194],"environment":[198],"demonstrating":[199],"an":[200,237,281],"enhancement":[201],"harmonics":[203],"suppression":[204],"91.3%.":[206],"Furthermore,":[207],"proposed":[209],"technique":[210],"exploited":[212],"subtracting":[217],"suppress":[228],"fundamental":[230,257],"frequency.":[231],"average":[238],"THD":[239],"119.5%,":[241],"while":[242],"conventional":[244,276],"Pulse":[245],"Amplitude":[246],"Modulation":[247],"(PAM)":[248],"method":[249],"71.22%":[251],"allowing":[252],"better":[254],"ratio.":[258],"These":[259],"open":[261],"door":[263],"implementation":[266],"comparable":[272],"quality":[273],"PAM":[277],"technique,":[278],"yet":[279],"increased":[282],"frame-rate":[283],"reduced":[285],"motion":[286],"artifacts.":[287]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
