{"id":"https://openalex.org/W4390722230","doi":"https://doi.org/10.1186/s40537-023-00858-6","title":"CNN-IKOA: convolutional neural network with improved Kepler optimization algorithm for image segmentation: experimental validation and numerical exploration","display_name":"CNN-IKOA: convolutional neural network with improved Kepler optimization algorithm for image segmentation: experimental validation and numerical exploration","publication_year":2024,"publication_date":"2024-01-10","ids":{"openalex":"https://openalex.org/W4390722230","doi":"https://doi.org/10.1186/s40537-023-00858-6"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-023-00858-6","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-023-00858-6","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-023-00858-6","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-023-00858-6","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079704928","display_name":"Mohamed Abdel\u2010Basset","orcid":"https://orcid.org/0000-0002-2794-3936"},"institutions":[{"id":"https://openalex.org/I192398990","display_name":"Zagazig University","ror":"https://ror.org/053g6we49","country_code":"EG","type":"education","lineage":["https://openalex.org/I192398990"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Mohamed Abdel-Basset","raw_affiliation_strings":["Faculty of Computers and Informatics, Zagazig University, Zagazig, 44519, Sharqiyah, Egypt"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Computers and Informatics, Zagazig University, Zagazig, 44519, Sharqiyah, Egypt","institution_ids":["https://openalex.org/I192398990"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079264025","display_name":"Reda Mohamed","orcid":"https://orcid.org/0000-0002-1903-4062"},"institutions":[{"id":"https://openalex.org/I192398990","display_name":"Zagazig University","ror":"https://ror.org/053g6we49","country_code":"EG","type":"education","lineage":["https://openalex.org/I192398990"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Reda Mohamed","raw_affiliation_strings":["Faculty of Computers and Informatics, Zagazig University, Zagazig, 44519, Sharqiyah, Egypt"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Computers and Informatics, Zagazig University, Zagazig, 44519, Sharqiyah, Egypt","institution_ids":["https://openalex.org/I192398990"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037428435","display_name":"Ibrahim Alrashdi","orcid":"https://orcid.org/0000-0001-7537-5542"},"institutions":[{"id":"https://openalex.org/I199702508","display_name":"Jouf University","ror":"https://ror.org/02zsyt821","country_code":"SA","type":"education","lineage":["https://openalex.org/I199702508"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Ibrahim Alrashdi","raw_affiliation_strings":["Department of Computer Science, College of Computer and Information Sciences, Jouf University, 2014, Sakaka, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, College of Computer and Information Sciences, Jouf University, 2014, Sakaka, Saudi Arabia","institution_ids":["https://openalex.org/I199702508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012051592","display_name":"Karam M. Sallam","orcid":"https://orcid.org/0000-0001-5767-2818"},"institutions":[{"id":"https://openalex.org/I188329596","display_name":"University of Canberra","ror":"https://ror.org/04s1nv328","country_code":"AU","type":"education","lineage":["https://openalex.org/I188329596"]},{"id":"https://openalex.org/I29891158","display_name":"University of Sharjah","ror":"https://ror.org/00engpz63","country_code":"AE","type":"education","lineage":["https://openalex.org/I29891158"]}],"countries":["AE","AU"],"is_corresponding":true,"raw_author_name":"Karam M. Sallam","raw_affiliation_strings":["Department of Computer Science, University of Sharjah, Sharjah, United Arab Emirates","School of IT and Systems, Faculty of Science and Technology, University of Canberra, Canberra, 2601, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Sharjah, Sharjah, United Arab Emirates","institution_ids":["https://openalex.org/I29891158"]},{"raw_affiliation_string":"School of IT and Systems, Faculty of Science and Technology, University of Canberra, Canberra, 2601, Australia","institution_ids":["https://openalex.org/I188329596"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047918826","display_name":"Ibrahim A. Hameed","orcid":"https://orcid.org/0000-0003-1252-260X"},"institutions":[{"id":"https://openalex.org/I204778367","display_name":"Norwegian University of Science and Technology","ror":"https://ror.org/05xg72x27","country_code":"NO","type":"education","lineage":["https://openalex.org/I204778367"]}],"countries":["NO"],"is_corresponding":true,"raw_author_name":"Ibrahim A. Hameed","raw_affiliation_strings":["Department of ICT and Natural Sciences, Norwegian University of Science and Technology (NTNU), 7491, \u00c5lesund, Norway"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of ICT and Natural Sciences, Norwegian University of Science and Technology (NTNU), 7491, \u00c5lesund, Norway","institution_ids":["https://openalex.org/I204778367"]}]}],"institutions":[],"countries_distinct_count":5,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5012051592","https://openalex.org/A5037428435","https://openalex.org/A5047918826"],"corresponding_institution_ids":["https://openalex.org/I188329596","https://openalex.org/I199702508","https://openalex.org/I204778367","https://openalex.org/I29891158"],"apc_list":{"value":1060,"currency":"GBP","value_usd":1300},"apc_paid":{"value":1060,"currency":"GBP","value_usd":1300},"fwci":9.8171,"has_fulltext":true,"cited_by_count":26,"citation_normalized_percentile":{"value":0.98553505,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"11","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":1.0,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9869999885559082,"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"}},{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9818999767303467,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7814759016036987},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7112152576446533},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6150758862495422},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.6063780188560486},{"id":"https://openalex.org/keywords/maxima-and-minima","display_name":"Maxima and minima","score":0.5632348656654358},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5629591941833496},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5628753900527954},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5536907911300659},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5437300801277161},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46872082352638245},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43408408761024475},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42996081709861755},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.41972413659095764},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1259547770023346}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7814759016036987},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7112152576446533},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6150758862495422},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.6063780188560486},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.5632348656654358},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5629591941833496},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5628753900527954},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5536907911300659},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5437300801277161},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46872082352638245},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43408408761024475},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42996081709861755},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41972413659095764},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1259547770023346},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s40537-023-00858-6","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-023-00858-6","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-023-00858-6","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5c338c7b76d94a4083ef4d8e96713160","is_oa":true,"landing_page_url":"https://doaj.org/article/5c338c7b76d94a4083ef4d8e96713160","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":"Journal of Big Data, Vol 11, Iss 1, Pp 1-31 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s40537-023-00858-6","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-023-00858-6","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-023-00858-6","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.5899999737739563,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4390722230.pdf"},"referenced_works_count":55,"referenced_works":["https://openalex.org/W1999284878","https://openalex.org/W2050787737","https://openalex.org/W2088821145","https://openalex.org/W2133059825","https://openalex.org/W2809254203","https://openalex.org/W2962949934","https://openalex.org/W2981338736","https://openalex.org/W2990426214","https://openalex.org/W3010846265","https://openalex.org/W3015108567","https://openalex.org/W3022894865","https://openalex.org/W3025011581","https://openalex.org/W3028699979","https://openalex.org/W3038102268","https://openalex.org/W3048749423","https://openalex.org/W3089168916","https://openalex.org/W3089911346","https://openalex.org/W3105081694","https://openalex.org/W3140022118","https://openalex.org/W3159622623","https://openalex.org/W3161570504","https://openalex.org/W3162620147","https://openalex.org/W3164185666","https://openalex.org/W3181491309","https://openalex.org/W3194248593","https://openalex.org/W3200668918","https://openalex.org/W3208125829","https://openalex.org/W3214729164","https://openalex.org/W4200096115","https://openalex.org/W4205860727","https://openalex.org/W4206931805","https://openalex.org/W4207037169","https://openalex.org/W4210661452","https://openalex.org/W4243046127","https://openalex.org/W4285098962","https://openalex.org/W4288067780","https://openalex.org/W4296336207","https://openalex.org/W4307293208","https://openalex.org/W4309635755","https://openalex.org/W4309892741","https://openalex.org/W4310073244","https://openalex.org/W4310497810","https://openalex.org/W4313476913","https://openalex.org/W4313479115","https://openalex.org/W4313857678","https://openalex.org/W4315498026","https://openalex.org/W4319444944","https://openalex.org/W4323048641","https://openalex.org/W4323922821","https://openalex.org/W4327704827","https://openalex.org/W4327967376","https://openalex.org/W4372311959","https://openalex.org/W4376107978","https://openalex.org/W4383336911","https://openalex.org/W4388017883"],"related_works":["https://openalex.org/W2016177008","https://openalex.org/W1968965685","https://openalex.org/W2012792772","https://openalex.org/W2356573839","https://openalex.org/W2009028679","https://openalex.org/W2357424838","https://openalex.org/W2356903262","https://openalex.org/W2327601824","https://openalex.org/W4237142086","https://openalex.org/W2161102362"],"abstract_inverted_index":{"Abstract":[0],"Chest":[1],"diseases,":[2],"especially":[3],"COVID-19,":[4],"have":[5,30,128,143],"quickly":[6],"spread":[7],"throughout":[8],"the":[9,66,77,93,101,125,153,168,189,199,216,256,262,266,290,293,311,317,325],"world":[10],"and":[11,18,115,162,205,233,305,344],"caused":[12],"many":[13],"deaths.":[14],"Finding":[15],"a":[16,57,136,280],"rapid":[17],"accurate":[19,132],"diagnostic":[20],"tool":[21],"was":[22],"indispensable":[23],"to":[24,42,81,91,111,130,148,196,214,242,278,287,309,316],"combating":[25],"these":[26,69,84,99],"diseases.":[27],"Therefore,":[28,86,141,174],"scientists":[29],"thought":[31],"of":[32,68,139,170,188,218,248,258,292],"combining":[33],"chest":[34,52],"X-ray":[35],"(CXR)":[36],"images":[37,201,211,270,326],"with":[38,47,121],"deep":[39,70],"learning":[40,71],"techniques":[41],"rapidly":[43],"detect":[44],"people":[45],"infected":[46],"COVID-19":[48],"or":[49],"any":[50],"other":[51],"disease.":[53],"Image":[54],"segmentation":[55,95,105,181,294],"as":[56,73,167],"preprocessing":[58],"step":[59],"has":[60],"an":[61,178,185],"essential":[62],"role":[63],"in":[64,135,246],"improving":[65],"performance":[67,217,250,297],"techniques,":[72],"it":[74,239,331],"could":[75,320,332],"separate":[76],"most":[78],"relevant":[79],"features":[80,134],"better":[82,197],"train":[83,279],"techniques.":[85],"several":[87,243,249],"approaches":[88],"were":[89],"proposed":[90,282],"tackle":[92,149],"image":[94,104,180],"problem":[96],"accurately.":[97],"Among":[98],"methods,":[100],"multilevel":[102],"thresholding-based":[103],"methods":[106,127],"won":[107],"significant":[108],"interest":[109],"due":[110],"their":[112],"simplicity,":[113],"accuracy,":[114,301,337],"relatively":[116],"low":[117],"storage":[118],"requirements.":[119],"However,":[120],"increasing":[122],"threshold":[123,171,207,222,274],"levels,":[124],"traditional":[126],"failed":[129],"achieve":[131,321],"segmented":[133,268,327],"reasonable":[137],"amount":[138],"time.":[140],"researchers":[142],"recently":[144],"used":[145,213,277,308],"metaheuristic":[146,244],"algorithms":[147,155,245],"this":[150,175],"problem,":[151],"but":[152],"existing":[154],"still":[156],"suffer":[157],"from":[158],"slow":[159],"convergence":[160],"speed":[161],"stagnation":[163],"into":[164],"local":[165],"minima":[166],"number":[169],"levels":[172,223,275],"increases.":[173],"study":[176],"presents":[177],"alternative":[179],"technique":[182],"based":[183],"on":[184],"enhanced":[186],"version":[187],"Kepler":[190],"optimization":[191],"algorithm":[192],"(KOA),":[193],"namely":[194,299],"IKOA,":[195],"segment":[198],"CXR":[200,210,269],"at":[202,220,271,328],"small,":[203],"medium,":[204],"high":[206],"levels.":[208],"Ten":[209],"are":[212,276,307],"assess":[215],"IKOA":[219,259],"ten":[221],"(T-5,":[224],"T-7,":[225],"T-8,":[226],"T-10,":[227],"T-12,":[228,329],"T-15,":[229],"T-18,":[230],"T-20,":[231],"T-25,":[232],"T-30).":[234],"To":[235],"observe":[236],"its":[237],"effectiveness,":[238],"is":[240],"compared":[241,263],"terms":[247],"indicators.":[251],"The":[252],"experimental":[253,318],"outcomes":[254,323],"disclose":[255,310],"superiority":[257],"over":[260],"all":[261],"algorithms.":[264],"Furthermore,":[265],"IKOA-based":[267],"eight":[272],"different":[273],"newly":[281],"CNN":[283],"model":[284],"called":[285],"CNN-IKOA":[286],"find":[288],"out":[289],"effectiveness":[291],"step.":[295],"Five":[296],"indicators,":[298],"overall":[300,336],"precision,":[302,343],"recall,":[303],"F1-score,":[304],"specificity,":[306,340],"CNN-IKOA\u2019s":[312],"effectiveness.":[313],"CNN-IKOA,":[314],"according":[315],"outcomes,":[319],"outstanding":[322],"for":[324,335,339,342,346],"where":[330],"reach":[333],"94.88%":[334],"96.57%":[338],"95.40%":[341,345],"recall.":[347]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":13}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
