{"id":"https://openalex.org/W2881583077","doi":"https://doi.org/10.1109/siu.2018.8404554","title":"Tongue contour extraction from ultrasound images using image parts","display_name":"Tongue contour extraction from ultrasound images using image parts","publication_year":2018,"publication_date":"2018-05-01","ids":{"openalex":"https://openalex.org/W2881583077","doi":"https://doi.org/10.1109/siu.2018.8404554","mag":"2881583077"},"language":"en","primary_location":{"id":"doi:10.1109/siu.2018.8404554","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2018.8404554","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th Signal Processing and Communications Applications Conference (SIU)","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/A5028554144","display_name":"Enes Aslan","orcid":"https://orcid.org/0000-0002-3204-4601"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Enes Aslan","raw_affiliation_strings":["Kuveyt T&#x00FC;rk Katilim Bankasi, AR-GE Merkezi, Kocaeli, T&#x00FC;rkiye"],"affiliations":[{"raw_affiliation_string":"Kuveyt T&#x00FC;rk Katilim Bankasi, AR-GE Merkezi, Kocaeli, T&#x00FC;rkiye","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058939919","display_name":"Naci Dumlu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Naci Dumlu","raw_affiliation_strings":["Pendik Devlet Hastanesi, Radyoloji B&#x00F6;l&#x00FC;m&#x00FC; istanbul, T&#x00FC;rkiye"],"affiliations":[{"raw_affiliation_string":"Pendik Devlet Hastanesi, Radyoloji B&#x00F6;l&#x00FC;m&#x00FC; istanbul, T&#x00FC;rkiye","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076768060","display_name":"Yusuf Sinan Akg\u00fcl","orcid":"https://orcid.org/0000-0001-8501-4812"},"institutions":[{"id":"https://openalex.org/I4210124062","display_name":"T\u00fcbitak National Metrology Institute","ror":"https://ror.org/02zcjdk53","country_code":"TR","type":"facility","lineage":["https://openalex.org/I4210124062"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Yusuf Sinan Akg\u00fcl","raw_affiliation_strings":["GIT Vision Lab, Bilgisayar M&#x00FC;hendisli&#x011F;i B&#x00F6;l&#x00FC;m&#x00FC;, Gebze Teknik &#x00DC;niversitesi, Kocaeli, 41400, T&#x00FC;rkiye"],"affiliations":[{"raw_affiliation_string":"GIT Vision Lab, Bilgisayar M&#x00FC;hendisli&#x011F;i B&#x00F6;l&#x00FC;m&#x00FC;, Gebze Teknik &#x00DC;niversitesi, Kocaeli, 41400, T&#x00FC;rkiye","institution_ids":["https://openalex.org/I4210124062"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5028554144"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6144,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.72847822,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12647","display_name":"Traditional Chinese Medicine Studies","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative 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/T12647","display_name":"Traditional Chinese Medicine Studies","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative 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/T10515","display_name":"Cancer-related molecular mechanisms research","score":0.9532999992370605,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11521","display_name":"Salivary Gland Disorders and Functions","score":0.9186000227928162,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8042265176773071},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7141472101211548},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6217858195304871},{"id":"https://openalex.org/keywords/tongue","display_name":"Tongue","score":0.6004325151443481},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5723757147789001},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5398082137107849},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4683629274368286},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.43397632241249084},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.42891746759414673},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.415131539106369}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8042265176773071},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7141472101211548},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6217858195304871},{"id":"https://openalex.org/C2779744641","wikidata":"https://www.wikidata.org/wiki/Q9614","display_name":"Tongue","level":2,"score":0.6004325151443481},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5723757147789001},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5398082137107849},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4683629274368286},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.43397632241249084},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.42891746759414673},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.415131539106369},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/siu.2018.8404554","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2018.8404554","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8299999833106995,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1585339076","https://openalex.org/W2016307665","https://openalex.org/W2136223099","https://openalex.org/W2155893237","https://openalex.org/W2963830389"],"related_works":["https://openalex.org/W3136794468","https://openalex.org/W2367950022","https://openalex.org/W2365707941","https://openalex.org/W2366141844","https://openalex.org/W2383946220","https://openalex.org/W2358428239","https://openalex.org/W3011636953","https://openalex.org/W2351206852","https://openalex.org/W3212410916","https://openalex.org/W3006862861"],"abstract_inverted_index":{"In":[0,29,70],"this":[1],"work":[2,147],"we":[3],"propose":[4],"automatic":[5],"tongue":[6,41,110,116,128],"contour":[7,42,117,129,155],"extraction":[8],"from":[9,39],"ultrasound":[10,26,165],"images":[11,56],"based":[12],"on":[13,141],"Convolutional":[14],"Neural":[15],"Networks":[16],"(CNN).":[17],"The":[18,127,146,161],"developed":[19],"deep":[20],"neural":[21],"network":[22],"was":[23,43,64],"trained":[24],"with":[25,156],"image":[27,36,75],"parts.":[28,126],"training":[30,67,90],"step":[31],"the":[32,35,46,53,61,71,74,80,89,109,115,121,125,152,157,169],"distances":[33],"of":[34,52,58,124,144,164],"patch":[37],"centers":[38,122],"nearest":[40],"used":[44,65],"as":[45,66,86],"class":[47,98],"label.":[48],"By":[49],"taking":[50],"advantage":[51],"fact":[54],"that":[55,99],"consist":[57],"video":[59],"frames,":[60],"time":[62],"information":[63],"input":[68,87],"parameter.":[69],"test":[72],"phase,":[73],"parts":[76],"obtained":[77],"by":[78,132,150],"using":[79,120],"sliding":[81],"window":[82],"method":[83],"are":[84,95],"given":[85],"to":[88,102,108],"model":[91],"and":[92],"distance":[93],"classes":[94],"obtained.":[96],"A":[97],"is":[100,130,148],"close":[101,107],"zero":[103],"means":[104],"a":[105,134],"position":[106],"contour.":[111,160],"Candidate":[112],"points":[113,123,143],"for":[114],"were":[118],"created":[119],"extracted":[131],"fitting":[133],"3":[135],"<sup":[136],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[137],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">rd</sup>":[138],"degree":[139],"polynomial":[140],"center":[142],"candidates.":[145],"completed":[149],"comparing":[151],"manually":[153],"marked":[154],"automatically":[158],"found":[159],"dataset":[162],"consists":[163],"videos":[166],"taken":[167],"in":[168],"experimental":[170],"environment.":[171]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}