{"id":"https://openalex.org/W2974383081","doi":"https://doi.org/10.1109/ic3.2019.8844937","title":"Classification of Breast Microscopic Imaging using Hybrid CLAHE-CNN Deep Architecture","display_name":"Classification of Breast Microscopic Imaging using Hybrid CLAHE-CNN Deep Architecture","publication_year":2019,"publication_date":"2019-08-01","ids":{"openalex":"https://openalex.org/W2974383081","doi":"https://doi.org/10.1109/ic3.2019.8844937","mag":"2974383081"},"language":"en","primary_location":{"id":"doi:10.1109/ic3.2019.8844937","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic3.2019.8844937","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Twelfth International Conference on Contemporary Computing (IC3)","raw_type":"proceedings-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/A5018737268","display_name":"Ankit Vidyarthi","orcid":"https://orcid.org/0000-0002-8026-4246"},"institutions":[{"id":"https://openalex.org/I154970844","display_name":"Jaypee Institute of Information Technology","ror":"https://ror.org/05sttyy11","country_code":"IN","type":"education","lineage":["https://openalex.org/I154970844"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Ankit Vidyarthi","raw_affiliation_strings":["Department of CSE&IT, Jaypee Institute of Information Technology, Noida, INDIA"],"affiliations":[{"raw_affiliation_string":"Department of CSE&IT, Jaypee Institute of Information Technology, Noida, INDIA","institution_ids":["https://openalex.org/I154970844"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019192098","display_name":"Jatin Shad","orcid":null},"institutions":[{"id":"https://openalex.org/I154970844","display_name":"Jaypee Institute of Information Technology","ror":"https://ror.org/05sttyy11","country_code":"IN","type":"education","lineage":["https://openalex.org/I154970844"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Jatin Shad","raw_affiliation_strings":["Department of CSE&IT, Jaypee Institute of Information Technology, Noida, INDIA"],"affiliations":[{"raw_affiliation_string":"Department of CSE&IT, Jaypee Institute of Information Technology, Noida, INDIA","institution_ids":["https://openalex.org/I154970844"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101916117","display_name":"Shubham Sharma","orcid":"https://orcid.org/0000-0003-3685-8706"},"institutions":[{"id":"https://openalex.org/I154970844","display_name":"Jaypee Institute of Information Technology","ror":"https://ror.org/05sttyy11","country_code":"IN","type":"education","lineage":["https://openalex.org/I154970844"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shubham Sharma","raw_affiliation_strings":["Department of CSE&IT, Jaypee Institute of Information Technology, Noida, INDIA"],"affiliations":[{"raw_affiliation_string":"Department of CSE&IT, Jaypee Institute of Information Technology, Noida, INDIA","institution_ids":["https://openalex.org/I154970844"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082124692","display_name":"Paridhi Agarwal","orcid":null},"institutions":[{"id":"https://openalex.org/I154970844","display_name":"Jaypee Institute of Information Technology","ror":"https://ror.org/05sttyy11","country_code":"IN","type":"education","lineage":["https://openalex.org/I154970844"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Paridhi Agarwal","raw_affiliation_strings":["Department of CSE&IT, Jaypee Institute of Information Technology, Noida, INDIA"],"affiliations":[{"raw_affiliation_string":"Department of CSE&IT, Jaypee Institute of Information Technology, Noida, INDIA","institution_ids":["https://openalex.org/I154970844"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5018737268"],"corresponding_institution_ids":["https://openalex.org/I154970844"],"apc_list":null,"apc_paid":null,"fwci":1.0127,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.83027289,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9998000264167786,"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":0.9998000264167786,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9853000044822693,"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/adaptive-histogram-equalization","display_name":"Adaptive histogram equalization","score":0.88057541847229},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7697240710258484},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6827825903892517},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6407018899917603},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5411919355392456},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.4529529809951782},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.4518458843231201},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4496968388557434},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43175333738327026},{"id":"https://openalex.org/keywords/histogram-equalization","display_name":"Histogram equalization","score":0.3858200013637543},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3706132769584656},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1707594394683838}],"concepts":[{"id":"https://openalex.org/C30387639","wikidata":"https://www.wikidata.org/wiki/Q4680744","display_name":"Adaptive histogram equalization","level":5,"score":0.88057541847229},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7697240710258484},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6827825903892517},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6407018899917603},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5411919355392456},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.4529529809951782},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.4518458843231201},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4496968388557434},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43175333738327026},{"id":"https://openalex.org/C136943445","wikidata":"https://www.wikidata.org/wiki/Q1970240","display_name":"Histogram equalization","level":4,"score":0.3858200013637543},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3706132769584656},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1707594394683838},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ic3.2019.8844937","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic3.2019.8844937","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Twelfth International Conference on Contemporary Computing (IC3)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2040599785","https://openalex.org/W2052550738","https://openalex.org/W2058333183","https://openalex.org/W2175543269","https://openalex.org/W2312404985","https://openalex.org/W2339885376","https://openalex.org/W2509926707","https://openalex.org/W2549267210","https://openalex.org/W2741675591","https://openalex.org/W2751723768","https://openalex.org/W2756270667","https://openalex.org/W2795013683","https://openalex.org/W2896790556","https://openalex.org/W2952367870","https://openalex.org/W6764657306"],"related_works":["https://openalex.org/W2162593906","https://openalex.org/W2387482914","https://openalex.org/W2385217229","https://openalex.org/W2302472796","https://openalex.org/W2376822833","https://openalex.org/W2393164332","https://openalex.org/W4319781082","https://openalex.org/W2015245117","https://openalex.org/W2604503469","https://openalex.org/W2381972374"],"abstract_inverted_index":{"Breast":[0],"cancer":[1,8,32],"is":[2,19,33,36,97,117,123,159],"the":[3,65,77,87,90,144,150,157,173,194],"most":[4,20],"prevalent":[5],"form":[6],"of":[7,30,44,80,89,104,112,118,128,135,164,203],"and":[9,15,82,115,132,154],"can":[10],"occur":[11],"in":[12,57,107,201],"both":[13],"men":[14],"women,":[16],"although":[17],"it":[18,35,39],"common":[21],"among":[22],"women.":[23],"The":[24,55,94,189],"problem":[25],"with":[26,99,125,131,137,161],"manual":[27],"pathology":[28],"examination":[29],"breast":[31,91],"that":[34,102,193],"time-consuming":[37],"as":[38,176],"requires":[40],"scanning":[41],"through":[42],"images":[43,106,111,136,151],"tissue":[45],"under":[46],"various":[47,70],"distinct":[48],"magnification":[49],"levels":[50],"to":[51,63,148],"obtain":[52],"accurate":[53],"diagnoses.":[54],"advancement":[56],"computer":[58],"assisted":[59],"diagnosis":[60,67],"system":[61],"help":[62],"improve":[64],"early":[66],"process":[68],"using":[69],"machine":[71],"learning":[72],"algorithms.":[73],"This":[74],"paper":[75],"proposes":[76],"hybrid":[78,162,196],"architecture":[79,96,147,163,185,197],"CLAHE":[81],"deep":[83],"convolutional":[84],"network":[85],"for":[86,179,186],"classification":[88],"microscopic":[92],"imaging.":[93],"proposed":[95,141,195],"experimented":[98,124],"BreakHis":[100],"dataset":[101],"comprises":[103],"7909":[105],"total":[108],"having":[109],"2480":[110],"benign":[113,153],"class":[114],"rest":[116],"malignant":[119],"class.":[120],"Proposed":[121],"method":[122,142],"two":[126],"level":[127],"test":[129],"i.e.,":[130],"without":[133],"pre-processing":[134,178],"CNN":[138,146,184],"architecture.":[139],"Initially,":[140],"uses":[143],"traditional":[145,199],"classify":[149],"into":[152],"malignant.":[155],"Later,":[156],"experiment":[158],"performed":[160],"Contrast":[165],"Limited":[166],"Adaptive":[167],"Histogram":[168],"Equalization":[169],"(CLAHE)":[170],"followed":[171,182],"by":[172,183],"watershed":[174],"algorithm,":[175],"a":[177],"image":[180,187],"enhancement":[181],"classification.":[188],"experimental":[190],"result":[191],"suggest":[192],"outperforms":[198],"methods":[200],"terms":[202],"accuracy":[204],"gained":[205],"around":[206],"3%.":[207]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-24T08:02:53.985720","created_date":"2025-10-10T00:00:00"}
