{"id":"https://openalex.org/W2766464270","doi":"https://doi.org/10.3233/his-170240","title":"Content-based mammogram retrieval using wavelet based complete-LBP and K-means clustering for the diagnosis of breast cancer","display_name":"Content-based mammogram retrieval using wavelet based complete-LBP and K-means clustering for the diagnosis of breast cancer","publication_year":2017,"publication_date":"2017-11-05","ids":{"openalex":"https://openalex.org/W2766464270","doi":"https://doi.org/10.3233/his-170240","mag":"2766464270"},"language":"en","primary_location":{"id":"doi:10.3233/his-170240","is_oa":false,"landing_page_url":"https://doi.org/10.3233/his-170240","pdf_url":null,"source":{"id":"https://openalex.org/S50927259","display_name":"International Journal of Hybrid Intelligent Systems","issn_l":"1448-5869","issn":["1448-5869","1875-8819"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Hybrid Intelligent 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/A5050934066","display_name":"Vibhav Prakash Singh","orcid":"https://orcid.org/0000-0002-6823-2524"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Vibhav Prakash Singh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5033457874","display_name":"Rajeev Srivastava","orcid":"https://orcid.org/0000-0002-0165-1556"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rajeev Srivastava","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5050934066"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3608,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.69296852,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"14","issue":"1-2","first_page":"31","last_page":"39"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9997000098228455,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9997000098228455,"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/T10862","display_name":"AI in cancer detection","score":0.9822999835014343,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.98089998960495,"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/computer-science","display_name":"Computer science","score":0.6646143198013306},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6624248027801514},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6472740769386292},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6336766481399536},{"id":"https://openalex.org/keywords/local-binary-patterns","display_name":"Local binary patterns","score":0.5948666334152222},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.511431872844696},{"id":"https://openalex.org/keywords/region-of-interest","display_name":"Region of interest","score":0.4915941655635834},{"id":"https://openalex.org/keywords/mammography","display_name":"Mammography","score":0.4804251194000244},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.47196638584136963},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.46937015652656555},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.46121156215667725},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.4460321068763733},{"id":"https://openalex.org/keywords/similarity-measure","display_name":"Similarity measure","score":0.44422757625579834},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4389117956161499},{"id":"https://openalex.org/keywords/k-means-clustering","display_name":"k-means clustering","score":0.4243111312389374},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4227710962295532},{"id":"https://openalex.org/keywords/content-based-image-retrieval","display_name":"Content-based image retrieval","score":0.4138134717941284},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.25025033950805664},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.247392475605011},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.16515624523162842},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.10408920049667358}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6646143198013306},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6624248027801514},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6472740769386292},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6336766481399536},{"id":"https://openalex.org/C87335442","wikidata":"https://www.wikidata.org/wiki/Q2494345","display_name":"Local binary patterns","level":4,"score":0.5948666334152222},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.511431872844696},{"id":"https://openalex.org/C19609008","wikidata":"https://www.wikidata.org/wiki/Q2138203","display_name":"Region of interest","level":2,"score":0.4915941655635834},{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.4804251194000244},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.47196638584136963},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.46937015652656555},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.46121156215667725},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.4460321068763733},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.44422757625579834},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4389117956161499},{"id":"https://openalex.org/C207968372","wikidata":"https://www.wikidata.org/wiki/Q310401","display_name":"k-means clustering","level":3,"score":0.4243111312389374},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4227710962295532},{"id":"https://openalex.org/C2780052074","wikidata":"https://www.wikidata.org/wiki/Q1128648","display_name":"Content-based image retrieval","level":4,"score":0.4138134717941284},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.25025033950805664},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.247392475605011},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.16515624523162842},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.10408920049667358},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/his-170240","is_oa":false,"landing_page_url":"https://doi.org/10.3233/his-170240","pdf_url":null,"source":{"id":"https://openalex.org/S50927259","display_name":"International Journal of Hybrid Intelligent Systems","issn_l":"1448-5869","issn":["1448-5869","1875-8819"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Hybrid Intelligent Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.7799999713897705,"display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1523069120","https://openalex.org/W2020216156","https://openalex.org/W2039051707","https://openalex.org/W2065814655","https://openalex.org/W2077832074","https://openalex.org/W2083799892","https://openalex.org/W2103496373","https://openalex.org/W2103718624","https://openalex.org/W2114581665","https://openalex.org/W2117853853","https://openalex.org/W2123318149","https://openalex.org/W2132549764","https://openalex.org/W2147141800","https://openalex.org/W2187991617","https://openalex.org/W2293457052","https://openalex.org/W2342550926","https://openalex.org/W2414040782","https://openalex.org/W2514575318","https://openalex.org/W2557798449","https://openalex.org/W2623286609","https://openalex.org/W2736459270","https://openalex.org/W2756619998","https://openalex.org/W3100816363","https://openalex.org/W4285719527","https://openalex.org/W6687151590","https://openalex.org/W6704710254","https://openalex.org/W6745155968"],"related_works":["https://openalex.org/W3003836766","https://openalex.org/W2005771019","https://openalex.org/W2486556835","https://openalex.org/W3021364800","https://openalex.org/W3165453100","https://openalex.org/W2207021851","https://openalex.org/W2285052147","https://openalex.org/W2914194627","https://openalex.org/W2185970706","https://openalex.org/W2893876445"],"abstract_inverted_index":{"Early":[0],"diagnosis":[1,31],"of":[2,32,61,67,85,109,121,213],"breast":[3,33],"cancer":[4,12,34],"can":[5],"improve":[6],"the":[7,37,65,86,114,135,153,156,167,176,179,201],"survival":[8],"rate":[9],"by":[10,35,50],"detecting":[11],"at":[13,152],"initial":[14],"stage.":[15],"In":[16],"this":[17,118,143],"paper,":[18],"an":[19],"efficient":[20],"content-based":[21],"mammogram":[22,40,87,125,158],"retrieval":[23,188],"system":[24],"is":[25,159,171],"proposed,":[26],"which":[27],"helps":[28],"in":[29,162,178],"early":[30],"classifying":[36],"current":[38],"case":[39],"and":[41,53,79,98,123,170],"retrieving":[42],"similar":[43],"pas":[44],"t":[45],"cases":[46],"mammograms":[47,62],"already":[48],"annotated":[49],"diagnostic":[51],"descriptions":[52],"treatment":[54],"results.":[55],"The":[56],"proposed":[57,202],"steps":[58],"include":[59],"cropping":[60],"for":[63],"finding":[64],"region":[66],"interest":[68],"(ROI),":[69],"feature":[70],"extraction":[71],"using":[72,90,146],"wavelet":[73,106],"based-complete":[74],"local":[75],"binary":[76],"pattern":[77],"(W-CLBP)":[78],"K-means":[80,112],"clustering.":[81],"Strong":[82],"texture":[83,119,214],"characteristics":[84],"are":[88,127,140],"captured":[89],"CLBP":[91],"to":[92,133,209],"all":[93,130,175],"detailed":[94],"coefficients":[95],"(LH,":[96],"HL,":[97],"HH)":[99],"from":[100,142],"two":[101],"level":[102],"decomposed":[103],"2":[104],"Dimensional-discrete":[105],"transform":[107],"(2D-DWT)":[108],"ROI.":[110],"Further,":[111],"generates":[113],"clusters":[115],"based":[116],"on":[117,191],"similarity":[120,149],"mammograms,":[122],"query":[124,157],"features":[126],"matched":[128],"with":[129,174,186,207],"cluster":[131,145,168],"representatives":[132],"find":[134],"closest":[136,144],"cluster.":[137],"Finally,":[138],"images":[139,177],"retrieved":[141],"Euclidean":[147],"distance":[148],"measure.":[150],"So,":[151],"searching":[154],"time":[155,185],"searched":[160],"only":[161],"small":[163],"sub-set":[164],"depending":[165],"upon":[166],"size":[169],"not":[172],"compared":[173],"database,":[180],"reflects":[181],"a":[182],"superior":[183],"response":[184],"good":[187],"performances.":[189],"Experiments":[190],"benchmark":[192],"mammography":[193],"image":[194],"analysis":[195],"Society":[196],"(MIAS)":[197],"database":[198],"confirm":[199],"that":[200],"method":[203],"has":[204],"better":[205],"say":[206],"respect":[208],"other":[210],"four":[211],"variants":[212],"features.":[215]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-23T06:36:01.041984","created_date":"2025-10-10T00:00:00"}