{"id":"https://openalex.org/W4391342116","doi":"https://doi.org/10.1109/access.2024.3360223","title":"Improved Segmentation Model for Melanoma Lesion Detection Using Normalized Cross-Correlation-Based <i>k</i>-Means Clustering","display_name":"Improved Segmentation Model for Melanoma Lesion Detection Using Normalized Cross-Correlation-Based <i>k</i>-Means Clustering","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4391342116","doi":"https://doi.org/10.1109/access.2024.3360223"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3360223","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3360223","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10416953.pdf","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","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://ieeexplore.ieee.org/ielx7/6287639/6514899/10416953.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071657559","display_name":"Muhammad Imran Faizi","orcid":"https://orcid.org/0009-0000-1293-3527"},"institutions":[{"id":"https://openalex.org/I173207729","display_name":"University of Engineering and Technology Taxila","ror":"https://ror.org/03v00ka07","country_code":"PK","type":"education","lineage":["https://openalex.org/I173207729"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Muhammad Imran Faizi","raw_affiliation_strings":["Department of Computer Sciences, University of Engineering and Technology Taxila, Taxila, Pakistan"],"raw_orcid":"https://orcid.org/0009-0000-1293-3527","affiliations":[{"raw_affiliation_string":"Department of Computer Sciences, University of Engineering and Technology Taxila, Taxila, Pakistan","institution_ids":["https://openalex.org/I173207729"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069324602","display_name":"Syed Muhammad Adnan","orcid":null},"institutions":[{"id":"https://openalex.org/I173207729","display_name":"University of Engineering and Technology Taxila","ror":"https://ror.org/03v00ka07","country_code":"PK","type":"education","lineage":["https://openalex.org/I173207729"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Syed Muhammad Adnan","raw_affiliation_strings":["Department of Computer Sciences, University of Engineering and Technology Taxila, Taxila, Pakistan"],"raw_orcid":"https://orcid.org/0000-0002-0254-412X","affiliations":[{"raw_affiliation_string":"Department of Computer Sciences, University of Engineering and Technology Taxila, Taxila, Pakistan","institution_ids":["https://openalex.org/I173207729"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I173207729"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":4.0444,"has_fulltext":true,"cited_by_count":17,"citation_normalized_percentile":{"value":0.95048979,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"12","issue":null,"first_page":"20753","last_page":"20766"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.9998000264167786,"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":0.9998000264167786,"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/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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9768999814987183,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8134052157402039},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7237251400947571},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6878042817115784},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6708850264549255},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6117618680000305},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5483461618423462},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.5408104062080383},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5318652391433716},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5199854969978333},{"id":"https://openalex.org/keywords/histogram-of-oriented-gradients","display_name":"Histogram of oriented gradients","score":0.45159316062927246},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44125890731811523},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.14794990420341492}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8134052157402039},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7237251400947571},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6878042817115784},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6708850264549255},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6117618680000305},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5483461618423462},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.5408104062080383},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5318652391433716},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5199854969978333},{"id":"https://openalex.org/C17426736","wikidata":"https://www.wikidata.org/wiki/Q419918","display_name":"Histogram of oriented gradients","level":4,"score":0.45159316062927246},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44125890731811523},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.14794990420341492}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3360223","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3360223","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10416953.pdf","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:769ae9fc20014c519cdc000354893381","is_oa":true,"landing_page_url":"https://doaj.org/article/769ae9fc20014c519cdc000354893381","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"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 12, Pp 20753-20766 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3360223","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3360223","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10416953.pdf","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391342116.pdf","grobid_xml":"https://content.openalex.org/works/W4391342116.grobid-xml"},"referenced_works_count":66,"referenced_works":["https://openalex.org/W1555598655","https://openalex.org/W1570448133","https://openalex.org/W1977838479","https://openalex.org/W2003260632","https://openalex.org/W2024476192","https://openalex.org/W2025432719","https://openalex.org/W2025983537","https://openalex.org/W2035167409","https://openalex.org/W2044465660","https://openalex.org/W2053164108","https://openalex.org/W2059238568","https://openalex.org/W2061576204","https://openalex.org/W2074472758","https://openalex.org/W2075433722","https://openalex.org/W2107074288","https://openalex.org/W2122111042","https://openalex.org/W2129661341","https://openalex.org/W2142259554","https://openalex.org/W2148587254","https://openalex.org/W2155632266","https://openalex.org/W2159498975","https://openalex.org/W2162515926","https://openalex.org/W2172169906","https://openalex.org/W2483714401","https://openalex.org/W2491179239","https://openalex.org/W2581082771","https://openalex.org/W2592160412","https://openalex.org/W2782684153","https://openalex.org/W2789357239","https://openalex.org/W2793691907","https://openalex.org/W2892053105","https://openalex.org/W2899268959","https://openalex.org/W2903060508","https://openalex.org/W2903950532","https://openalex.org/W2907688358","https://openalex.org/W2911964244","https://openalex.org/W2917303411","https://openalex.org/W2919115771","https://openalex.org/W2919345074","https://openalex.org/W2932083555","https://openalex.org/W2940027968","https://openalex.org/W2963059730","https://openalex.org/W2998249562","https://openalex.org/W3006913750","https://openalex.org/W3009382903","https://openalex.org/W3024334774","https://openalex.org/W3034356437","https://openalex.org/W3037339707","https://openalex.org/W3089739901","https://openalex.org/W3097337942","https://openalex.org/W3118471509","https://openalex.org/W3118741778","https://openalex.org/W3209833153","https://openalex.org/W4212777832","https://openalex.org/W4220785415","https://openalex.org/W4220926832","https://openalex.org/W4236137412","https://openalex.org/W4239510810","https://openalex.org/W4248483482","https://openalex.org/W4253444893","https://openalex.org/W4298001327","https://openalex.org/W4304693539","https://openalex.org/W4317770553","https://openalex.org/W4321242408","https://openalex.org/W4361018635","https://openalex.org/W6689896248"],"related_works":["https://openalex.org/W4367336074","https://openalex.org/W3154045278","https://openalex.org/W4379620016","https://openalex.org/W4393666307","https://openalex.org/W3210764983","https://openalex.org/W4393443811","https://openalex.org/W4367335949","https://openalex.org/W3089416646","https://openalex.org/W4396816114","https://openalex.org/W4380048833"],"abstract_inverted_index":{"The":[0,31,91,232,261],"most":[1],"unexpected":[2],"and":[3,51,62,84,123,145,168,223,235,248,258,276,281],"fatal":[4],"kind":[5],"of":[6,20,34,57,109,115,133,245],"cancer,":[7],"melanoma,":[8],"has":[9],"been":[10],"on":[11,250],"the":[12,21,40,106,113,138,154,172,182,190,194,200,242,251,288],"rise":[13],"in":[14,181],"its":[15,28,37],"spread":[16],"to":[17,54,67,104,137,153,185,202,240,272],"different":[18],"parts":[19],"body.":[22],"Early":[23],"detection":[24],"can":[25,81],"significantly":[26],"reduce":[27],"fatality":[29],"rate.":[30],"primary":[32],"stages":[33],"melanoma":[35,86],"for":[36,157,165,230],"identification":[38],"by":[39,98],"unaided":[41],"eye":[42],"are":[43,228],"a":[44,55,60,77],"difficult":[45],"task":[46],"that":[47,80],"demands":[48],"extensive":[49],"training":[50],"understanding.":[52],"Due":[53],"lack":[56],"qualified":[58],"dermatologists,":[59],"computerized":[61],"automated":[63],"method":[64,162],"is":[65,135,147,151,163,179],"required":[66],"correctly":[68],"detect":[69,83],"melanoma.":[70],"This":[71],"study":[72],"achieved":[73],"this":[74],"feat":[75],"through":[76],"proposed":[78,183,262],"system":[79,184],"effectively":[82],"classify":[85],"as":[87,112,206],"benign":[88],"or":[89,208],"malignant.":[90],"process":[92],"begins":[93],"with":[94],"image":[95,156],"template":[96],"matching":[97],"using":[99],"normalized":[100,264],"cross-correlation":[101],"technique":[102],"induction":[103],"mark":[105],"infected":[107],"area":[108],"skin":[110,196,204],"lesion":[111],"region":[114],"interest":[116],"(ROI)":[117],"from":[118,171,193,287],"ISIC":[119],"datasets":[120,255],"2017,":[121],"2019,":[122],"2020":[124],"dermoscopic":[125,253],"images.":[126,289],"Our":[127],"novel":[128],"model":[129],"dynamically":[130],"calculated":[131],"number":[132],"clusters":[134],"assigned":[136],"<italic":[139],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[140],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">k</i>":[141],"-means":[142],"clustering":[143,268],"algorithm,":[144],"ROI":[146],"extracted.":[148],"Histogram":[149],"equalization":[150],"applied":[152],"output":[155],"contrast":[158],"enhancement.":[159],"Hu":[160],"Moment":[161],"implemented":[164],"shape":[166],"classification":[167],"part":[169],"recognition":[170],"segmented":[173,195],"image.":[174],"GLCM-based":[175],"Haralick":[176],"feature":[177,191,285],"extractor":[178],"used":[180,229],"extract":[186],"textural":[187],"features":[188],"generating":[189],"vector":[192],"lesion.":[197],"It":[198],"leads":[199],"classifier":[201],"identify":[203],"lesions":[205],"cancerous":[207],"non-cancerous.":[209],"Random":[210,236],"Forest,":[211],"Decision":[212],"Tree,":[213],"Support":[214],"Vector":[215],"Machine":[216],"(SVM),":[217],"Gaussian":[218],"Na\u00efve":[219],"Bayes,":[220],"Logistic":[221],"Regression,":[222],"K-Nearest":[224],"Neighbor":[225],"(KNN)":[226],"Classifiers":[227],"classification.":[231],"KNN,":[233],"SVM":[234],"Forest":[237],"was":[238,270],"successful":[239],"attain":[241],"highest":[243],"accuracy":[244],"99.29%,":[246],"99.38%":[247],"99.46%":[249],"given":[252],"images":[254],"ISIC-2019,":[256],"ISIC-2020":[257],"ISIC-2017":[259],"respectively.":[260],"method,":[263],"cross":[265],"correlation-based":[266],"k-means":[267],"model,":[269],"found":[271],"be":[273],"more":[274,284],"robust":[275],"accurate":[277],"than":[278],"existing":[279],"methods":[280],"incorporates":[282],"much":[283],"information":[286]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":3}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}