{"id":"https://openalex.org/W3116593018","doi":"https://doi.org/10.1109/apccas50809.2020.9301710","title":"Automatic Tongue Image Segmentation Based on Thresholding and an Improved Level Set Model","display_name":"Automatic Tongue Image Segmentation Based on Thresholding and an Improved Level Set Model","publication_year":2020,"publication_date":"2020-12-08","ids":{"openalex":"https://openalex.org/W3116593018","doi":"https://doi.org/10.1109/apccas50809.2020.9301710","mag":"3116593018"},"language":"en","primary_location":{"id":"doi:10.1109/apccas50809.2020.9301710","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apccas50809.2020.9301710","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)","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/A5101110347","display_name":"Hongyu Gu","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongyu Gu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101593079","display_name":"Zhecheng Yang","orcid":"https://orcid.org/0000-0002-6364-2559"},"institutions":[{"id":"https://openalex.org/I4210148850","display_name":"National Science Library","ror":"https://ror.org/04ndjyr10","country_code":"CN","type":"archive","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210148850"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhecheng Yang","raw_affiliation_strings":["National Laboratory for Information Science and Technology, Beijing, China","Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory for Information Science and Technology, Beijing, China","institution_ids":["https://openalex.org/I4210148850"]},{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100420459","display_name":"Hong Chen","orcid":"https://orcid.org/0000-0003-0774-1410"},"institutions":[{"id":"https://openalex.org/I4210148850","display_name":"National Science Library","ror":"https://ror.org/04ndjyr10","country_code":"CN","type":"archive","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210148850"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Chen","raw_affiliation_strings":["National Laboratory for Information Science and Technology, Beijing, China","Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory for Information Science and Technology, Beijing, China","institution_ids":["https://openalex.org/I4210148850"]},{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101110347"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.9395,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.78962603,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"149","last_page":"152"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12647","display_name":"Traditional Chinese Medicine Studies","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9009000062942505,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.7894637584686279},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7740393877029419},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7131009697914124},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6543012857437134},{"id":"https://openalex.org/keywords/tongue","display_name":"Tongue","score":0.6393104195594788},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5984469652175903},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5943480134010315},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5906717777252197},{"id":"https://openalex.org/keywords/active-contour-model","display_name":"Active contour model","score":0.5372310876846313},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4968452751636505},{"id":"https://openalex.org/keywords/geodesic","display_name":"Geodesic","score":0.4592115879058838},{"id":"https://openalex.org/keywords/level-set","display_name":"Level set (data structures)","score":0.42648208141326904},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3485018014907837},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2308855652809143}],"concepts":[{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.7894637584686279},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7740393877029419},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7131009697914124},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6543012857437134},{"id":"https://openalex.org/C2779744641","wikidata":"https://www.wikidata.org/wiki/Q9614","display_name":"Tongue","level":2,"score":0.6393104195594788},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5984469652175903},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5943480134010315},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5906717777252197},{"id":"https://openalex.org/C112353826","wikidata":"https://www.wikidata.org/wiki/Q127313","display_name":"Active contour model","level":4,"score":0.5372310876846313},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4968452751636505},{"id":"https://openalex.org/C165818556","wikidata":"https://www.wikidata.org/wiki/Q213488","display_name":"Geodesic","level":2,"score":0.4592115879058838},{"id":"https://openalex.org/C153008295","wikidata":"https://www.wikidata.org/wiki/Q6535093","display_name":"Level set (data structures)","level":2,"score":0.42648208141326904},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3485018014907837},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2308855652809143},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/apccas50809.2020.9301710","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apccas50809.2020.9301710","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.8500000238418579,"display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2104095591","https://openalex.org/W2116040950","https://openalex.org/W2126494533","https://openalex.org/W2133059825","https://openalex.org/W2134820502","https://openalex.org/W2219813377","https://openalex.org/W2606318859","https://openalex.org/W2769143887","https://openalex.org/W2896532114","https://openalex.org/W2943849814","https://openalex.org/W2982258507","https://openalex.org/W3008970117","https://openalex.org/W3211330693"],"related_works":["https://openalex.org/W2006673626","https://openalex.org/W2368150111","https://openalex.org/W2125739208","https://openalex.org/W185820115","https://openalex.org/W2098360446","https://openalex.org/W2382233853","https://openalex.org/W2888165508","https://openalex.org/W2168406752","https://openalex.org/W3023152879","https://openalex.org/W2766054123"],"abstract_inverted_index":{"Tongue":[0],"diagnosis":[1,8,23],"is":[2,17,33,54,81,94,110,136],"an":[3,28,67],"important":[4],"and":[5,50,77,113,149],"widely":[6],"used":[7],"method":[9,46],"in":[10,19,62,143],"traditional":[11],"Chinese":[12],"medicine.":[13],"Automatic":[14],"tongue":[15,22,30,141],"segmentation":[16,31],"crucial":[18],"the":[20,41,58,63,91,107,116],"digital":[21],"system.":[24],"In":[25,40],"this":[26],"paper,":[27],"automatic":[29],"algorithm":[32,135],"proposed,":[34],"which":[35,56],"consists":[36],"of":[37,90,100,125,133,145],"two":[38,101],"steps.":[39],"first":[42],"step,":[43],"a":[44,97,120],"thresholding":[45],"that":[47,106],"combines":[48],"color":[49],"gray":[51],"level":[52,69],"information":[53],"designed,":[55],"provides":[57],"initial":[59],"contour":[60,76],"needed":[61],"second":[64],"step.":[65],"Next,":[66],"improved":[68],"set":[70],"model":[71,80,93],"based":[72],"on":[73],"geodesic":[74],"active":[75],"Chan":[78],"Vese":[79],"put":[82],"forward":[83],"for":[84,96],"boundary":[85],"refinement.":[86],"The":[87,131],"weight":[88],"function":[89],"new":[92],"adapted":[95],"better":[98],"balance":[99],"sub-models.":[102],"Experiment":[103],"results":[104],"show":[105],"segmented":[108],"area":[109],"more":[111],"complete":[112],"closer":[114],"to":[115],"real":[117],"target":[118],"with":[119,128],"lowest":[121],"average":[122],"ME":[123],"value":[124],"0.081":[126],"compared":[127],"other":[129],"methods.":[130],"robustness":[132],"our":[134],"also":[137],"verified":[138],"by":[139],"different":[140],"images":[142],"terms":[144],"shapes,":[146],"lighting":[147],"conditions":[148],"resolutions.":[150]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}