{"id":"https://openalex.org/W2799460839","doi":"https://doi.org/10.1109/tmi.2018.2829662","title":"Photoacoustic Source Detection and Reflection Artifact Removal Enabled by Deep Learning","display_name":"Photoacoustic Source Detection and Reflection Artifact Removal Enabled by Deep Learning","publication_year":2018,"publication_date":"2018-04-23","ids":{"openalex":"https://openalex.org/W2799460839","doi":"https://doi.org/10.1109/tmi.2018.2829662","mag":"2799460839","pmid":"https://pubmed.ncbi.nlm.nih.gov/29870374"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2018.2829662","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tmi.2018.2829662","pdf_url":"https://ieeexplore.ieee.org/ielx7/42/8370207/08345287.pdf","source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://ieeexplore.ieee.org/ielx7/42/8370207/08345287.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039001114","display_name":"Derek Allman","orcid":"https://orcid.org/0000-0002-9614-5823"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Derek Allman","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA"],"raw_orcid":"https://orcid.org/0000-0002-9614-5823","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073346635","display_name":"Austin Reiter","orcid":null},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Austin Reiter","raw_affiliation_strings":["Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003188378","display_name":"Muyinatu A. Lediju Bell","orcid":"https://orcid.org/0000-0002-8394-4482"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Muyinatu A. Lediju Bell","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA"],"raw_orcid":"https://orcid.org/0000-0002-8394-4482","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5039001114"],"corresponding_institution_ids":["https://openalex.org/I145311948"],"apc_list":null,"apc_paid":null,"fwci":13.0379,"has_fulltext":true,"cited_by_count":233,"citation_normalized_percentile":{"value":0.99326858,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"37","issue":"6","first_page":"1464","last_page":"1477"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":1.0,"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"}},{"id":"https://openalex.org/T11856","display_name":"Thermography and Photoacoustic Techniques","score":0.9940999746322632,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9524000287055969,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artifact","display_name":"Artifact (error)","score":0.7973694801330566},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7742428779602051},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6207504868507385},{"id":"https://openalex.org/keywords/imaging-phantom","display_name":"Imaging phantom","score":0.604505181312561},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5695199966430664},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5591816902160645},{"id":"https://openalex.org/keywords/point-source","display_name":"Point source","score":0.4854060113430023},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.478943407535553},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4729875326156616},{"id":"https://openalex.org/keywords/photoacoustic-imaging-in-biomedicine","display_name":"Photoacoustic imaging in biomedicine","score":0.46141183376312256},{"id":"https://openalex.org/keywords/reflection","display_name":"Reflection (computer programming)","score":0.4471721947193146},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44111573696136475},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.41833949089050293},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4174025058746338},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34611424803733826},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.20704805850982666},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.17240315675735474},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1333695650100708},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10449811816215515}],"concepts":[{"id":"https://openalex.org/C2779010991","wikidata":"https://www.wikidata.org/wiki/Q2720909","display_name":"Artifact (error)","level":2,"score":0.7973694801330566},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7742428779602051},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6207504868507385},{"id":"https://openalex.org/C104293457","wikidata":"https://www.wikidata.org/wiki/Q28324852","display_name":"Imaging phantom","level":2,"score":0.604505181312561},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5695199966430664},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5591816902160645},{"id":"https://openalex.org/C103783831","wikidata":"https://www.wikidata.org/wiki/Q2552709","display_name":"Point source","level":2,"score":0.4854060113430023},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.478943407535553},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4729875326156616},{"id":"https://openalex.org/C54932901","wikidata":"https://www.wikidata.org/wiki/Q7187705","display_name":"Photoacoustic imaging in biomedicine","level":2,"score":0.46141183376312256},{"id":"https://openalex.org/C65682993","wikidata":"https://www.wikidata.org/wiki/Q1056451","display_name":"Reflection (computer programming)","level":2,"score":0.4471721947193146},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44111573696136475},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.41833949089050293},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4174025058746338},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34611424803733826},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.20704805850982666},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.17240315675735474},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1333695650100708},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10449811816215515},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D016477","descriptor_name":"Artifacts","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016477","descriptor_name":"Artifacts","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016477","descriptor_name":"Artifacts","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D061088","descriptor_name":"Photoacoustic Techniques","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D061088","descriptor_name":"Photoacoustic Techniques","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D061088","descriptor_name":"Photoacoustic Techniques","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1109/tmi.2018.2829662","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tmi.2018.2829662","pdf_url":"https://ieeexplore.ieee.org/ielx7/42/8370207/08345287.pdf","source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},{"id":"pmid:29870374","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/29870374","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on medical imaging","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:6075868","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6075868","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Trans Med Imaging","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1109/tmi.2018.2829662","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tmi.2018.2829662","pdf_url":"https://ieeexplore.ieee.org/ielx7/42/8370207/08345287.pdf","source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G470759646","display_name":null,"funder_award_id":"EB018994","funder_id":"https://openalex.org/F4320337363","funder_display_name":"National Institute of Biomedical Imaging and Bioengineering"},{"id":"https://openalex.org/G5017721915","display_name":null,"funder_award_id":"ECCS 1751522","funder_id":"https://openalex.org/F4320337392","funder_display_name":"Division of Electrical, Communications and Cyber Systems"},{"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/G681066976","display_name":null,"funder_award_id":"1751522","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/F4320337363","display_name":"National Institute of Biomedical Imaging and Bioengineering","ror":"https://ror.org/00372qc85"},{"id":"https://openalex.org/F4320337392","display_name":"Division of Electrical, Communications and Cyber Systems","ror":"https://ror.org/01krpsy48"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2799460839.pdf","grobid_xml":"https://content.openalex.org/works/W2799460839.grobid-xml"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W629875043","https://openalex.org/W639708223","https://openalex.org/W1492966311","https://openalex.org/W1536680647","https://openalex.org/W1686810756","https://openalex.org/W1769707307","https://openalex.org/W1970322047","https://openalex.org/W1995562189","https://openalex.org/W2023074414","https://openalex.org/W2030964111","https://openalex.org/W2040257390","https://openalex.org/W2054178107","https://openalex.org/W2058532431","https://openalex.org/W2062974097","https://openalex.org/W2084784875","https://openalex.org/W2091384557","https://openalex.org/W2097956757","https://openalex.org/W2099355420","https://openalex.org/W2102605133","https://openalex.org/W2116258003","https://openalex.org/W2120615054","https://openalex.org/W2141668152","https://openalex.org/W2155893237","https://openalex.org/W2157048271","https://openalex.org/W2162473564","https://openalex.org/W2163605009","https://openalex.org/W2296508705","https://openalex.org/W2313458468","https://openalex.org/W2331341581","https://openalex.org/W2332587343","https://openalex.org/W2560492130","https://openalex.org/W2575372681","https://openalex.org/W2593238072","https://openalex.org/W2594231052","https://openalex.org/W2750096260","https://openalex.org/W2771026226","https://openalex.org/W2790288617","https://openalex.org/W2792553245","https://openalex.org/W2793141590","https://openalex.org/W3104251514","https://openalex.org/W3105741497","https://openalex.org/W6620707391","https://openalex.org/W6637373629","https://openalex.org/W6674902714","https://openalex.org/W6684191040","https://openalex.org/W6697289314","https://openalex.org/W6698641161","https://openalex.org/W6734521152","https://openalex.org/W6749411571","https://openalex.org/W6891851673"],"related_works":["https://openalex.org/W52840052","https://openalex.org/W3162837891","https://openalex.org/W1687852313","https://openalex.org/W3029243869","https://openalex.org/W2502336004","https://openalex.org/W1741504538","https://openalex.org/W2417440389","https://openalex.org/W4308623176","https://openalex.org/W4244157427","https://openalex.org/W4230676417"],"abstract_inverted_index":{"Interventional":[0],"applications":[1],"of":[2,8,18,33,63,155,179,231,258,262],"photoacoustic":[3,39,70,292],"imaging":[4,141,266],"typically":[5],"require":[6],"visualization":[7],"point-like":[9,26],"targets,":[10],"such":[11],"as":[12,48],"the":[13,31,37,232,259,272],"small,":[14],"circular,":[15],"cross-sectional":[16],"tips":[17],"needles,":[19],"catheters,":[20],"or":[21,157],"brachytherapy":[22],"seeds.":[23],"When":[24],"these":[25,61],"targets":[27],"are":[28],"imaged":[29],"in":[30,68,91,125,138,163,278],"presence":[32],"highly":[34],"echogenic":[35],"structures,":[36],"resulting":[38],"wave":[40],"creates":[41],"a":[42,49,76,121,160,279],"reflection":[43,289],"artifact":[44,104],"that":[45,219,271],"may":[46],"appear":[47],"true":[50],"signal.":[51],"We":[52,169,268],"propose":[53],"to":[54,59,84,134,198,286],"use":[55],"deep":[56],"learning":[57],"techniques":[58],"identify":[60],"types":[62,178],"noise":[64,133],"artifacts":[65,90,290],"for":[66,150,247],"removal":[67],"experimental":[69,199,251],"data.":[71],"To":[72],"achieve":[73],"this":[74],"goal,":[75],"convolutional":[77],"neural":[78],"network":[79],"(CNN)":[80],"was":[81,237],"first":[82],"trained":[83,191],"locate":[85],"and":[86,89,102,110,129,176,182,201,206,242,249],"classify":[87],"sources":[88,128,175],"pre-beamformed":[92],"data":[93,194,203],"simulated":[94,193],"with":[95,105,159,173,186,192,204,298],"-Wave.":[96],"Simulations":[97],"initially":[98],"contained":[99],"one":[100,103,228],"source":[101,208,234],"various":[106],"medium":[107],"sound":[108],"speeds":[109],"2-D":[111],"target":[112],"locations.":[113],"Based":[114],"on":[115],"3,468":[116],"test":[117],"images,":[118,293],"we":[119,143],"achieved":[120,144,183],"100%":[122,205],"success":[123,148,185],"rate":[124],"classifying":[126],"both":[127],"artifacts.":[130],"After":[131],"adding":[132],"assess":[135],"potential":[136],"performance":[137,164],"more":[139],"realistic":[140],"environments,":[142],"at":[145,217],"least":[146],"98%":[147],"rates":[149],"channel":[151,167],"signal-to-noise":[152],"ratios":[153],"(SNRs)":[154],"-9dB":[156],"greater,":[158],"severe":[161],"decrease":[162],"below":[165],"-21dB":[166],"SNR.":[168],"then":[170,196],"explored":[171],"training":[172],"multiple":[174],"two":[177],"acoustic":[180],"receivers":[181],"similar":[184],"detecting":[187],"point":[188,233],"sources.":[189],"Networks":[190],"were":[195,215,220],"transferred":[197],"waterbath":[200,248],"phantom":[202,250],"96.67%":[207],"classification":[209],"accuracy,":[210],"respectively":[211],"(particularly":[212],"when":[213],"networks":[214],"tested":[216],"depths":[218],"included":[221],"during":[222],"training).":[223],"The":[224],"corresponding":[225],"mean":[226],"\u00b1":[227,239,244],"standard":[229],"deviation":[230],"location":[235],"error":[236],"0.40":[238],"0.22":[240],"mm":[241,246],"0.38":[243],"0.25":[245],"data,":[252],"respectively,":[253],"which":[254,294],"provides":[255],"some":[256],"indication":[257],"resolution":[260],"limits":[261],"our":[263],"new":[264],"CNN-based":[265,273],"system.":[267],"finally":[269],"show":[270],"information":[274],"can":[275],"be":[276],"displayed":[277],"novel":[280],"artifact-free":[281],"image":[282],"format,":[283],"enabling":[284],"us":[285],"effectively":[287],"remove":[288],"from":[291],"is":[295],"not":[296],"possible":[297],"traditional":[299],"geometry-based":[300],"beamforming.":[301]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":24},{"year":2024,"cited_by_count":19},{"year":2023,"cited_by_count":35},{"year":2022,"cited_by_count":32},{"year":2021,"cited_by_count":42},{"year":2020,"cited_by_count":46},{"year":2019,"cited_by_count":25},{"year":2018,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}