{"id":"https://openalex.org/W3014282405","doi":"https://doi.org/10.1109/access.2020.2984392","title":"Energy Noise Detection FCM for Breast Tumor Image Segmentation","display_name":"Energy Noise Detection FCM for Breast Tumor Image Segmentation","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3014282405","doi":"https://doi.org/10.1109/access.2020.2984392","mag":"3014282405"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.2984392","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2984392","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2020.2984392","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059850893","display_name":"Leyi Xiao","orcid":"https://orcid.org/0000-0002-7343-2256"},"institutions":[{"id":"https://openalex.org/I4610292","display_name":"Xiangtan University","ror":"https://ror.org/00xsfaz62","country_code":"CN","type":"education","lineage":["https://openalex.org/I4610292"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Leyi Xiao","raw_affiliation_strings":["Key Laboratory of Intelligent Computing and Information Processing, Ministry of Education, Xiangtan University, Xiangtan, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Computing and Information Processing, Ministry of Education, Xiangtan University, Xiangtan, China","institution_ids":["https://openalex.org/I4610292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100717222","display_name":"Qi Han","orcid":"https://orcid.org/0000-0001-9432-3131"},"institutions":[{"id":"https://openalex.org/I4610292","display_name":"Xiangtan University","ror":"https://ror.org/00xsfaz62","country_code":"CN","type":"education","lineage":["https://openalex.org/I4610292"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han Qi","raw_affiliation_strings":["Key Laboratory of Intelligent Computing and Information Processing, Ministry of Education, Xiangtan University, Xiangtan, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Computing and Information Processing, Ministry of Education, Xiangtan University, Xiangtan, China","institution_ids":["https://openalex.org/I4610292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014747562","display_name":"Chaodong Fan","orcid":"https://orcid.org/0000-0002-9829-0899"},"institutions":[{"id":"https://openalex.org/I169019527","display_name":"Quanzhou Normal University","ror":"https://ror.org/006ak0b38","country_code":"CN","type":"education","lineage":["https://openalex.org/I169019527"]},{"id":"https://openalex.org/I4610292","display_name":"Xiangtan University","ror":"https://ror.org/00xsfaz62","country_code":"CN","type":"education","lineage":["https://openalex.org/I4610292"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaodong Fan","raw_affiliation_strings":["Fujian Provincial Key Laboratory of Data Intensive Computing, Quanzhou Normal University, Quanzhou, China","Key Laboratory of Intelligent Computing and Information Processing, Ministry of Education, Xiangtan University, Xiangtan, China"],"affiliations":[{"raw_affiliation_string":"Fujian Provincial Key Laboratory of Data Intensive Computing, Quanzhou Normal University, Quanzhou, China","institution_ids":["https://openalex.org/I169019527"]},{"raw_affiliation_string":"Key Laboratory of Intelligent Computing and Information Processing, Ministry of Education, Xiangtan University, Xiangtan, China","institution_ids":["https://openalex.org/I4610292"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037811885","display_name":"Zhaoyang Ai","orcid":"https://orcid.org/0000-0002-3066-7733"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoyang Ai","raw_affiliation_strings":["College of Foreign Languages, Institute of Cognitive Control and Biophysics Linguistics, Hunan University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Foreign Languages, Institute of Cognitive Control and Biophysics Linguistics, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5059850893"],"corresponding_institution_ids":["https://openalex.org/I4610292"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.3977,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.67272232,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"8","issue":null,"first_page":"62895","last_page":"62904"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10862","display_name":"AI in cancer detection","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.995199978351593,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9940000176429749,"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/computer-science","display_name":"Computer science","score":0.6931904554367065},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6813299655914307},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6456369757652283},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6414039134979248},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.624902606010437},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5983772873878479},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5876001715660095},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5241363644599915},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.512117862701416},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4983689785003662},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.4455743134021759},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.44002389907836914},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.41533809900283813},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.41016319394111633},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.3760957717895508},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23360031843185425},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21557623147964478},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07891538739204407}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6931904554367065},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6813299655914307},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6456369757652283},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6414039134979248},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.624902606010437},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5983772873878479},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5876001715660095},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5241363644599915},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.512117862701416},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4983689785003662},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.4455743134021759},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.44002389907836914},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41533809900283813},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.41016319394111633},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.3760957717895508},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23360031843185425},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21557623147964478},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07891538739204407},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.2984392","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2984392","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:a4c356dda0e84950b42e7068a18f5fc5","is_oa":true,"landing_page_url":"https://doaj.org/article/a4c356dda0e84950b42e7068a18f5fc5","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 62895-62904 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.2984392","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2984392","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.8500000238418579}],"awards":[{"id":"https://openalex.org/G2848836474","display_name":null,"funder_award_id":"2016JJ3125","funder_id":"https://openalex.org/F4320322843","funder_display_name":"Natural Science Foundation of\u00a0Hunan Province"}],"funders":[{"id":"https://openalex.org/F4320322843","display_name":"Natural Science Foundation of\u00a0Hunan Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1589895371","https://openalex.org/W1992147426","https://openalex.org/W2012742622","https://openalex.org/W2027656446","https://openalex.org/W2036528686","https://openalex.org/W2106873791","https://openalex.org/W2108859253","https://openalex.org/W2130838651","https://openalex.org/W2290265371","https://openalex.org/W2419659284","https://openalex.org/W2473655448","https://openalex.org/W2487273947","https://openalex.org/W2551604932","https://openalex.org/W2586944109","https://openalex.org/W2786902820","https://openalex.org/W2787220232","https://openalex.org/W2803524673","https://openalex.org/W2890817474","https://openalex.org/W2900597592","https://openalex.org/W2930749509","https://openalex.org/W2936610935","https://openalex.org/W2946027615","https://openalex.org/W2952243269","https://openalex.org/W2956324374","https://openalex.org/W2965898445","https://openalex.org/W2966350350","https://openalex.org/W2979459011","https://openalex.org/W2981165461","https://openalex.org/W2990303645","https://openalex.org/W2991844793","https://openalex.org/W2993119222","https://openalex.org/W2999748665","https://openalex.org/W3007132505","https://openalex.org/W3008774220","https://openalex.org/W3009238340","https://openalex.org/W3110835628","https://openalex.org/W6676004750"],"related_works":["https://openalex.org/W3144569342","https://openalex.org/W2945274617","https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W2055202857","https://openalex.org/W4205800335","https://openalex.org/W2371519352","https://openalex.org/W2386644571","https://openalex.org/W2372421320","https://openalex.org/W2901890255"],"abstract_inverted_index":{"The":[0,103],"traditional":[1,119],"fuzzy":[2,26],"C@hyphenmeans":[3,27],"(FCM)":[4],"algorithm":[5,29,47,109],"ignores":[6],"the":[7,42,46,49,52,63,68,73,84,90,100,108,118,129],"spatial":[8,53,69],"information":[9,50],"of":[10,51,92],"pixels":[11],"and":[12,66,114,121,125],"is":[13,96],"sensitive":[14],"to":[15,56,76,88],"noise":[16,33,59],"images.":[17,133],"To":[18],"overcome":[19],"this":[20,22],"disadvantage,":[21],"paper":[23],"proposes":[24],"a":[25],"clustering":[28,101],"based":[30],"on":[31,41],"energy":[32,64],"detection":[34],"(ENDFCM)":[35],"for":[36],"mammographic":[37],"image":[38],"segmentation.":[39],"Based":[40],"weighted":[43],"mean":[44],"filtering,":[45],"employs":[48],"pixel":[54],"points":[55],"enhance":[57],"its":[58,78,93,122],"resistance.":[60],"By":[61],"introducing":[62],"curve":[65],"designing":[67],"distance,":[70],"it":[71,82],"constrains":[72],"objective":[74],"function":[75,87],"increase":[77,89],"parameter":[79],"adaptability.":[80],"Then,":[81],"derives":[83],"new":[85],"subordinate":[86],"relevance":[91],"subordinacy,":[94],"which":[95],"updated":[97],"continuously":[98],"during":[99],"process.":[102],"experimental":[104],"results":[105],"show":[106],"that":[107],"has":[110],"better":[111],"segmentation":[112],"accuracy":[113],"robustness":[115],"compared":[116],"with":[117],"FCM":[120],"improved":[123],"methods,":[124],"can":[126],"accurately":[127],"segment":[128],"noisy":[130],"breast":[131],"tumor":[132]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}