{"id":"https://openalex.org/W3097981864","doi":"https://doi.org/10.1515/bams-2020-0040","title":"A novel melanoma detection model: adapted K-means clustering-based segmentation process","display_name":"A novel melanoma detection model: adapted K-means clustering-based segmentation process","publication_year":2020,"publication_date":"2020-11-12","ids":{"openalex":"https://openalex.org/W3097981864","doi":"https://doi.org/10.1515/bams-2020-0040","mag":"3097981864"},"language":"en","primary_location":{"id":"doi:10.1515/bams-2020-0040","is_oa":false,"landing_page_url":"https://doi.org/10.1515/bams-2020-0040","pdf_url":null,"source":{"id":"https://openalex.org/S2764861201","display_name":"Bio-Algorithms and Med-Systems","issn_l":"1895-9091","issn":["1895-9091","1896-530X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310313990","host_organization_name":"De Gruyter","host_organization_lineage":["https://openalex.org/P4310313990"],"host_organization_lineage_names":["De Gruyter"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bio-Algorithms and Med-Systems","raw_type":"journal-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/A5024602976","display_name":"S. T. Sukanya","orcid":null},"institutions":[{"id":"https://openalex.org/I96797292","display_name":"Noorul Islam University","ror":"https://ror.org/01y2gf490","country_code":"IN","type":"education","lineage":["https://openalex.org/I96797292"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"S. T. Sukanya","raw_affiliation_strings":["Noorul Islam Centre for Higher Education , Kanyakumari , India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Noorul Islam Centre for Higher Education , Kanyakumari , India","institution_ids":["https://openalex.org/I96797292"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035199989","display_name":"S. Jerine","orcid":"https://orcid.org/0000-0002-4696-7204"},"institutions":[{"id":"https://openalex.org/I96797292","display_name":"Noorul Islam University","ror":"https://ror.org/01y2gf490","country_code":"IN","type":"education","lineage":["https://openalex.org/I96797292"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Jerine","raw_affiliation_strings":["Noorul Islam Centre for Higher Education , Kanyakumari , India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Noorul Islam Centre for Higher Education , Kanyakumari , India","institution_ids":["https://openalex.org/I96797292"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5024602976"],"corresponding_institution_ids":["https://openalex.org/I96797292"],"apc_list":null,"apc_paid":null,"fwci":0.3408,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.62019414,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":"17","issue":"2","first_page":"103","last_page":"118"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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/T12994","display_name":"Infrared Thermography in Medicine","score":0.9850999712944031,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T11144","display_name":"melanin and skin pigmentation","score":0.9731000065803528,"subfield":{"id":"https://openalex.org/subfields/1307","display_name":"Cell Biology"},"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/centroid","display_name":"Centroid","score":0.7642952799797058},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7178415060043335},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6968676447868347},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6803252696990967},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6516956686973572},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5940899848937988},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5137373208999634},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.45186641812324524},{"id":"https://openalex.org/keywords/k-means-clustering","display_name":"k-means clustering","score":0.41619637608528137},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.41046226024627686},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.29806041717529297}],"concepts":[{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.7642952799797058},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7178415060043335},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6968676447868347},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6803252696990967},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6516956686973572},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5940899848937988},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5137373208999634},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.45186641812324524},{"id":"https://openalex.org/C207968372","wikidata":"https://www.wikidata.org/wiki/Q310401","display_name":"k-means clustering","level":3,"score":0.41619637608528137},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.41046226024627686},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.29806041717529297}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1515/bams-2020-0040","is_oa":false,"landing_page_url":"https://doi.org/10.1515/bams-2020-0040","pdf_url":null,"source":{"id":"https://openalex.org/S2764861201","display_name":"Bio-Algorithms and Med-Systems","issn_l":"1895-9091","issn":["1895-9091","1896-530X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310313990","host_organization_name":"De Gruyter","host_organization_lineage":["https://openalex.org/P4310313990"],"host_organization_lineage_names":["De Gruyter"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bio-Algorithms and Med-Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W2048576056","https://openalex.org/W2055077797","https://openalex.org/W2059652177","https://openalex.org/W2092347923","https://openalex.org/W2159058417","https://openalex.org/W2286378748","https://openalex.org/W2306666006","https://openalex.org/W2316254880","https://openalex.org/W2342989150","https://openalex.org/W2589055215","https://openalex.org/W2765745871","https://openalex.org/W2802629662","https://openalex.org/W2807736567","https://openalex.org/W2808320397","https://openalex.org/W2808761706","https://openalex.org/W2887497095","https://openalex.org/W2891064068","https://openalex.org/W2895302468","https://openalex.org/W2899839556","https://openalex.org/W2900653857","https://openalex.org/W2908104276","https://openalex.org/W2910567234","https://openalex.org/W2911412294","https://openalex.org/W2922760433","https://openalex.org/W2932315469","https://openalex.org/W2946796433","https://openalex.org/W2948993742","https://openalex.org/W2962949934","https://openalex.org/W2964240917","https://openalex.org/W2965381342","https://openalex.org/W2968318837","https://openalex.org/W2969380645","https://openalex.org/W2969546126","https://openalex.org/W2972588473","https://openalex.org/W2986609444","https://openalex.org/W2990343796","https://openalex.org/W2996490063","https://openalex.org/W2996717109","https://openalex.org/W3003217150","https://openalex.org/W3005998039","https://openalex.org/W3011470554","https://openalex.org/W3037154692","https://openalex.org/W3047724182","https://openalex.org/W4249386356","https://openalex.org/W4249680802","https://openalex.org/W4252177401"],"related_works":["https://openalex.org/W2952821581","https://openalex.org/W4311618633","https://openalex.org/W2921411205","https://openalex.org/W2185776155","https://openalex.org/W4379648054","https://openalex.org/W2604976738","https://openalex.org/W2592235592","https://openalex.org/W2904779692","https://openalex.org/W3049268462","https://openalex.org/W2528614819"],"abstract_inverted_index":{"Abstract":[0],"Objectives":[1],"The":[2,102],"main":[3],"intention":[4],"of":[5,77,89,99,144,178],"this":[6,44],"paper":[7,24,45],"is":[8,73,84,105,148,168,182,185,213],"to":[9,131],"propose":[10],"a":[11,26,47,61],"new":[12,27,48,62],"Improved":[13,49],"K-means":[14,50,196],"clustering":[15,51],"algorithm,":[16,52],"by":[17,60,154],"optimally":[18,58],"tuning":[19],"the":[20,54,81,87,109,142,145,157,165,172,176,179,191,202,210,222],"centroids.":[21],"Methods":[22],"This":[23],"introduces":[25,46],"melanoma":[28,138,217],"detection":[29],"model":[30,147,212],"that":[31,170,209],"includes":[32],"three":[33],"major":[34],"phase\u2019s":[35],"viz.":[36],"segmentation,":[37,43],"feature":[38,106],"extraction":[39],"and":[40,97,115,187,197],"detection.":[41,139],"For":[42],"where":[53,108],"initial":[55],"centroids":[56],"are":[57,121,127],"tuned":[59],"algorithm":[63],"termed":[64],"Lion":[65],"Algorithm":[66],"with":[67],"New":[68],"Mating":[69],"Process":[70],"(LANM),":[71],"which":[72,184],"an":[74],"improved":[75],"version":[76],"standard":[78],"LA.":[79],"Moreover,":[80],"optimal":[82],"selection":[83],"based":[85],"on":[86],"consideration":[88],"multi-objective":[90],"including":[91],"intensity":[92],"diverse":[93],"centroid,":[94],"spatial":[95],"map,":[96],"frequency":[98],"occurrence,":[100],"respectively.":[101,199],"subsequent":[103],"phase":[104],"extraction,":[107],"proposed":[110,146,211],"Local":[111],"Vector":[112],"Pattern":[113],"(LVP)":[114],"Grey-Level":[116],"Co-Occurrence":[117],"Matrix":[118],"(GLCM)-based":[119],"features":[120,126],"extracted.":[122],"Further,":[123],"these":[124],"extracted":[125],"fed":[128],"as":[129,159,161],"input":[130],"Deep":[132],"Convolution":[133],"Neural":[134],"Network":[135],"(DCNN)":[136],"for":[137,171],"Results":[140],"Finally,":[141],"performance":[143],"evaluated":[149],"over":[150,221],"other":[151],"conventional":[152],"models":[153],"determining":[155],"both":[156],"positive":[158],"well":[160],"negative":[162],"measures.":[163],"From":[164,201],"analysis,":[166],"it":[167,205],"observed":[169,208],"normal":[173],"skin":[174],"image,":[175],"accuracy":[177],"presented":[180],"work":[181],"0.86379,":[183],"47.83%":[186],"0.245%":[188],"better":[189],"than":[190],"traditional":[192],"works":[193],"like":[194],"Conventional":[195],"PA-MSA,":[198],"Conclusions":[200],"overall":[203],"analysis":[204],"can":[206],"be":[207],"more":[214],"robust":[215],"in":[216],"prediction,":[218],"when":[219],"compared":[220],"state-of-art":[223],"models.":[224]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2026-05-21T09:19:25.381259","created_date":"2025-10-10T00:00:00"}
