{"id":"https://openalex.org/W2995563912","doi":"https://doi.org/10.23919/spa.2019.8936788","title":"CTCs extraction method based on frequency-domain filtering from microscope images","display_name":"CTCs extraction method based on frequency-domain filtering from microscope images","publication_year":2019,"publication_date":"2019-09-01","ids":{"openalex":"https://openalex.org/W2995563912","doi":"https://doi.org/10.23919/spa.2019.8936788","mag":"2995563912"},"language":"en","primary_location":{"id":"doi:10.23919/spa.2019.8936788","is_oa":false,"landing_page_url":"https://doi.org/10.23919/spa.2019.8936788","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5030035129","display_name":"Yoshida Kento","orcid":null},"institutions":[{"id":"https://openalex.org/I161296585","display_name":"Tokyo University of Science","ror":"https://ror.org/05sj3n476","country_code":"JP","type":"education","lineage":["https://openalex.org/I161296585"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kento Yoshida","raw_affiliation_strings":["Faculty of Industrial Science and Technology, Tokyo University of Science"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Industrial Science and Technology, Tokyo University of Science","institution_ids":["https://openalex.org/I161296585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020136239","display_name":"Yin\u2010Ju Chen","orcid":"https://orcid.org/0000-0001-9516-9463"},"institutions":[{"id":"https://openalex.org/I2802331550","display_name":"Taipei Medical University Hospital","ror":"https://ror.org/03k0md330","country_code":"TW","type":"healthcare","lineage":["https://openalex.org/I2802331550"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yin-Ju Chen","raw_affiliation_strings":["Graduate Institute of Biomedical Materials and Tissue Engineering, Taipei Medical University Hospital"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate Institute of Biomedical Materials and Tissue Engineering, Taipei Medical University Hospital","institution_ids":["https://openalex.org/I2802331550"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102970094","display_name":"Long\u2010Sheng Lu","orcid":"https://orcid.org/0000-0002-4247-1981"},"institutions":[{"id":"https://openalex.org/I2802331550","display_name":"Taipei Medical University Hospital","ror":"https://ror.org/03k0md330","country_code":"TW","type":"healthcare","lineage":["https://openalex.org/I2802331550"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Long-Sheng Lu","raw_affiliation_strings":["Graduate Institute of Biomedical Materials and Tissue Engineering, Taipei Medical University Hospital"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate Institute of Biomedical Materials and Tissue Engineering, Taipei Medical University Hospital","institution_ids":["https://openalex.org/I2802331550"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016789715","display_name":"Shin Aoki","orcid":"https://orcid.org/0000-0002-4287-6487"},"institutions":[{"id":"https://openalex.org/I161296585","display_name":"Tokyo University of Science","ror":"https://ror.org/05sj3n476","country_code":"JP","type":"education","lineage":["https://openalex.org/I161296585"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shin Aoki","raw_affiliation_strings":["Faculty of Pharmaceutical Sciences, Tokyo University of Science"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Pharmaceutical Sciences, Tokyo University of Science","institution_ids":["https://openalex.org/I161296585"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009469559","display_name":"Naoyuki Aikawa","orcid":null},"institutions":[{"id":"https://openalex.org/I161296585","display_name":"Tokyo University of Science","ror":"https://ror.org/05sj3n476","country_code":"JP","type":"education","lineage":["https://openalex.org/I161296585"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Naoyuki Aikawa","raw_affiliation_strings":["Faculty of Industrial Science and Technology, Tokyo University of Science"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Industrial Science and Technology, Tokyo University of Science","institution_ids":["https://openalex.org/I161296585"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0915,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.39444298,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"2019","issue":null,"first_page":"186","last_page":"191"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9966999888420105,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9966999888420105,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9952999949455261,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/honeycomb","display_name":"Honeycomb","score":0.646779477596283},{"id":"https://openalex.org/keywords/microscope","display_name":"Microscope","score":0.6012236475944519},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5901807546615601},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5770177841186523},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5752277970314026},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5464826822280884},{"id":"https://openalex.org/keywords/texture","display_name":"Texture (cosmology)","score":0.5229119658470154},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.5058862566947937},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48093101382255554},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.4688105881214142},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4569975733757019},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.45194390416145325},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.4447677731513977},{"id":"https://openalex.org/keywords/microscopy","display_name":"Microscopy","score":0.42948848009109497},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.30947986245155334},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.25211840867996216},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.19304543733596802},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.111530601978302},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.10906195640563965},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.07276064157485962}],"concepts":[{"id":"https://openalex.org/C145665481","wikidata":"https://www.wikidata.org/wiki/Q123339","display_name":"Honeycomb","level":2,"score":0.646779477596283},{"id":"https://openalex.org/C67649825","wikidata":"https://www.wikidata.org/wiki/Q196538","display_name":"Microscope","level":2,"score":0.6012236475944519},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5901807546615601},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5770177841186523},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5752277970314026},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5464826822280884},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.5229119658470154},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.5058862566947937},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48093101382255554},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.4688105881214142},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4569975733757019},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.45194390416145325},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.4447677731513977},{"id":"https://openalex.org/C147080431","wikidata":"https://www.wikidata.org/wiki/Q1074953","display_name":"Microscopy","level":2,"score":0.42948848009109497},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.30947986245155334},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.25211840867996216},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.19304543733596802},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.111530601978302},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.10906195640563965},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.07276064157485962},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.23919/spa.2019.8936788","is_oa":false,"landing_page_url":"https://doi.org/10.23919/spa.2019.8936788","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)","raw_type":"proceedings-article"},{"id":"mag:3090244508","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002247291066315","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8799999952316284,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2003099669","https://openalex.org/W2026470677","https://openalex.org/W2061052400","https://openalex.org/W2078718577","https://openalex.org/W2079428383","https://openalex.org/W2099244020","https://openalex.org/W2101818435","https://openalex.org/W2169632044","https://openalex.org/W2228912402","https://openalex.org/W2342708800","https://openalex.org/W2344654247","https://openalex.org/W2594171236","https://openalex.org/W2782049363","https://openalex.org/W2806375082","https://openalex.org/W2811092417","https://openalex.org/W2917728795","https://openalex.org/W2996868574","https://openalex.org/W4285719527","https://openalex.org/W6734662864","https://openalex.org/W6747514236"],"related_works":["https://openalex.org/W2329500892","https://openalex.org/W28991112","https://openalex.org/W2370726991","https://openalex.org/W2369710579","https://openalex.org/W2044270176","https://openalex.org/W2374828682","https://openalex.org/W2153116791","https://openalex.org/W2388733570","https://openalex.org/W4230530180","https://openalex.org/W1980033651"],"abstract_inverted_index":{"Circulating":[0],"tumor":[1],"cells":[2],"(CTCs)":[3],"can":[4,86],"be":[5],"used":[6],"for":[7,58,108],"the":[8,16,43,50,89,93,96,111,117],"early":[9],"detection":[10,36],"of":[11,15,18,95],"cancer":[12],"and":[13,34],"determination":[14],"effectiveness":[17],"anticancer":[19],"drug":[20],"treatment.":[21],"Sometimes":[22],"CTC":[23],"grows":[24],"on":[25],"a":[26,31,54,70,104],"culture":[27],"medium":[28],"which":[29],"has":[30],"honeycomb":[32,44,59,75,90],"texture,":[33],"existing":[35],"methods":[37],"cannot":[38],"achieve":[39],"satisfactory":[40],"results":[41],"because":[42],"textures":[45,60],"are":[46,98],"more":[47,114],"salient":[48,115],"than":[49,116],"CTCs":[51,55,118],"edges.":[52,119],"Thus,":[53],"extraction":[56],"method":[57,102],"from":[61,77],"microscope":[62,78],"images":[63,109],"is":[64,113],"needed.In":[65],"this":[66],"paper,":[67],"we":[68],"propose":[69],"new":[71],"algorithm":[72,85],"to":[73],"remove":[74,88],"texture":[76,91],"images.":[79],"We":[80],"confirmed":[81],"that":[82],"our":[83,101],"proposed":[84],"sufficiently":[87],"even":[92],"periodicity":[94],"patterns":[97],"weak.":[99],"Also":[100],"achieves":[103],"high":[105],"segmentation":[106],"accuracy":[107],"where":[110],"background":[112]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
