{"id":"https://openalex.org/W4293739722","doi":"https://doi.org/10.1142/s0218001422400055","title":"Liver Tumor Classification Using Optimal Opposition-Based Grey Wolf Optimization","display_name":"Liver Tumor Classification Using Optimal Opposition-Based Grey Wolf Optimization","publication_year":2022,"publication_date":"2022-08-31","ids":{"openalex":"https://openalex.org/W4293739722","doi":"https://doi.org/10.1142/s0218001422400055"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001422400055","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001422400055","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","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/A5103066492","display_name":"Reshma Jose","orcid":"https://orcid.org/0000-0002-5029-2035"},"institutions":[{"id":"https://openalex.org/I119668213","display_name":"Karunya University","ror":"https://ror.org/03k23nv15","country_code":"IN","type":"education","lineage":["https://openalex.org/I119668213"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Reshma Jose","raw_affiliation_strings":["Department of Electronics and Communication Engineering, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India","institution_ids":["https://openalex.org/I119668213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016190996","display_name":"Shanty Chacko","orcid":"https://orcid.org/0000-0003-1888-1283"},"institutions":[{"id":"https://openalex.org/I119668213","display_name":"Karunya University","ror":"https://ror.org/03k23nv15","country_code":"IN","type":"education","lineage":["https://openalex.org/I119668213"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shanty Chacko","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India","institution_ids":["https://openalex.org/I119668213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103089826","display_name":"J. Jayakumar","orcid":"https://orcid.org/0000-0001-7099-0554"},"institutions":[{"id":"https://openalex.org/I119668213","display_name":"Karunya University","ror":"https://ror.org/03k23nv15","country_code":"IN","type":"education","lineage":["https://openalex.org/I119668213"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"J. Jayakumar","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India","institution_ids":["https://openalex.org/I119668213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011636947","display_name":"T. Jarin","orcid":"https://orcid.org/0009-0005-5186-2748"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"T. Jarin","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, Jyothi Engineering College, Thrissur Kerala, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, Jyothi Engineering College, Thrissur Kerala, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103066492"],"corresponding_institution_ids":["https://openalex.org/I119668213"],"apc_list":null,"apc_paid":null,"fwci":0.6614,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.67950912,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"36","issue":"16","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9948999881744385,"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"}},"topics":[{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9948999881744385,"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/T10862","display_name":"AI in cancer detection","score":0.9944999814033508,"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/T13693","display_name":"Smart Systems and Machine Learning","score":0.9904000163078308,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.791075587272644},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5938926935195923},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5929304361343384},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5661996006965637},{"id":"https://openalex.org/keywords/adaptive-histogram-equalization","display_name":"Adaptive histogram equalization","score":0.5548683404922485},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.48338809609413147},{"id":"https://openalex.org/keywords/histogram-equalization","display_name":"Histogram equalization","score":0.47821375727653503},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45138978958129883},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4345473051071167},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.42367643117904663},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.40131473541259766},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2267809808254242}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.791075587272644},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5938926935195923},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5929304361343384},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5661996006965637},{"id":"https://openalex.org/C30387639","wikidata":"https://www.wikidata.org/wiki/Q4680744","display_name":"Adaptive histogram equalization","level":5,"score":0.5548683404922485},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.48338809609413147},{"id":"https://openalex.org/C136943445","wikidata":"https://www.wikidata.org/wiki/Q1970240","display_name":"Histogram equalization","level":4,"score":0.47821375727653503},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45138978958129883},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4345473051071167},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.42367643117904663},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.40131473541259766},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2267809808254242},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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:10.1142/s0218001422400055","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001422400055","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","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":26,"referenced_works":["https://openalex.org/W2061438946","https://openalex.org/W2072955302","https://openalex.org/W2096789844","https://openalex.org/W2100645706","https://openalex.org/W2127503402","https://openalex.org/W2738900493","https://openalex.org/W2792035544","https://openalex.org/W2897666251","https://openalex.org/W2959687571","https://openalex.org/W2973359219","https://openalex.org/W2993206503","https://openalex.org/W3007464329","https://openalex.org/W3010749409","https://openalex.org/W3015693563","https://openalex.org/W3046824133","https://openalex.org/W3099361481","https://openalex.org/W3107733281","https://openalex.org/W3112494578","https://openalex.org/W3118577024","https://openalex.org/W3124564723","https://openalex.org/W3129160290","https://openalex.org/W3134447168","https://openalex.org/W3190968905","https://openalex.org/W3194757953","https://openalex.org/W4221073034","https://openalex.org/W4229597740"],"related_works":["https://openalex.org/W2057981026","https://openalex.org/W2256021896","https://openalex.org/W2122866860","https://openalex.org/W2165297163","https://openalex.org/W2398368608","https://openalex.org/W1583737874","https://openalex.org/W2024449420","https://openalex.org/W1994424557","https://openalex.org/W3084145657","https://openalex.org/W4309786676"],"abstract_inverted_index":{"Image":[0],"processing":[1],"plays":[2],"a":[3,45,53,57,200],"significant":[4],"role":[5],"in":[6,31,49,91],"various":[7,27],"fields":[8],"like":[9],"military,":[10],"business,":[11],"healthcare":[12],"and":[13,21,105,141,159,191,208],"science.":[14],"Ultrasound":[15],"(US),":[16],"Magnetic":[17],"Resonance":[18],"Imaging":[19],"(MRI)":[20],"Computed":[22],"Tomography":[23],"(CT)":[24],"are":[25,144,155,194],"the":[26,32,35,38,79,93,106,125,135,148,180,183],"image":[28],"tests":[29,43],"used":[30,77,132],"treatment":[33],"of":[34,81,182,203,206,213],"cancer.":[36,83],"Detecting":[37],"liver":[39,82,115],"tumor":[40,136],"by":[41,98,110,118],"these":[42,153],"is":[44,61,64,76,96,108,116,131,161,170,186],"complex":[46],"process.":[47,151],"Hence,":[48],"this":[50],"research":[51],"work,":[52],"novel":[54],"approach":[55],"utilizing":[56],"deep":[58],"learning":[59],"model":[60],"used.":[62],"That":[63],"Deep":[65],"Belief":[66],"Network":[67],"(DBN)":[68],"with":[69],"Opposition-Based":[70],"Learning":[71],"(OBL)-Grey":[72],"Wolf":[73],"Optimization":[74],"(GWO)":[75],"for":[78],"classification":[80],"This":[84],"process":[85],"undergoes":[86],"five":[87],"major":[88],"processes.":[89],"Initially,":[90],"pre-processing":[92],"color":[94],"contrast":[95],"improved":[97],"Contrast":[99],"Limited":[100],"Adaptive":[101],"Histogram":[102],"Equalization":[103],"(CLAHE)":[104],"noise":[107],"removed":[109],"Wiener":[111],"Filtering":[112],"(WF).":[113],"The":[114,138,167,196],"segmented":[117],"adaptive":[119],"thresholding":[120],"following":[121],"pre-processing.":[122],"Following":[123],"that,":[124],"kernelizedFuzzy":[126],"C":[127],"Means":[128],"(FCM)":[129],"method":[130],"to":[133,163,188],"segment":[134],"area.":[137],"form,":[139],"color,":[140],"texture":[142],"features":[143],"then":[145],"extracted":[146],"during":[147],"feature":[149],"extraction":[150],"Finally,":[152,179],"traits":[154],"categorized":[156],"using":[157],"DBN,":[158],"OBL-GWO":[160],"employed":[162],"enhance":[164],"system":[165],"performance.":[166],"entire":[168],"evaluation":[169],"done":[171],"on":[172],"Liver":[173],"Tumor":[174],"Segmentation":[175],"(LiTS)":[176],"benchmark":[177],"dataset.":[178],"performance":[181],"proposed":[184,197],"DBN-OBL-GWO":[185,198],"compared":[187],"other":[189],"models":[190],"their":[192],"achievements":[193],"proved.":[195],"achieves":[199],"better":[201],"accuracy":[202],"0.995,":[204],"precision":[205],"0.948":[207],"false":[209],"positive":[210],"rate":[211],"(FPR)":[212],"0.116,":[214],"respectively.":[215]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}