{"id":"https://openalex.org/W2439179533","doi":"https://doi.org/10.1109/ncvpripg.2015.7490068","title":"Classification of brain MR images using discrete wavelet transform and random forests","display_name":"Classification of brain MR images using discrete wavelet transform and random forests","publication_year":2015,"publication_date":"2015-12-01","ids":{"openalex":"https://openalex.org/W2439179533","doi":"https://doi.org/10.1109/ncvpripg.2015.7490068","mag":"2439179533"},"language":"en","primary_location":{"id":"doi:10.1109/ncvpripg.2015.7490068","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ncvpripg.2015.7490068","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Fifth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","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/A5046512961","display_name":"Deepak Ranjan Nayak","orcid":"https://orcid.org/0000-0002-8929-5778"},"institutions":[{"id":"https://openalex.org/I16292982","display_name":"National Institute of Technology Rourkela","ror":"https://ror.org/011gmn932","country_code":"IN","type":"education","lineage":["https://openalex.org/I16292982"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Deepak Ranjan Nayak","raw_affiliation_strings":["Department of Computer Science and Engineering, National Institute of Technology, Rourkela, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, National Institute of Technology, Rourkela, India","institution_ids":["https://openalex.org/I16292982"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025838508","display_name":"Ratnakar Dash","orcid":"https://orcid.org/0000-0001-9886-2546"},"institutions":[{"id":"https://openalex.org/I16292982","display_name":"National Institute of Technology Rourkela","ror":"https://ror.org/011gmn932","country_code":"IN","type":"education","lineage":["https://openalex.org/I16292982"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ratnakar Dash","raw_affiliation_strings":["Department of Computer Science and Engineering, National Institute of Technology, Rourkela, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, National Institute of Technology, Rourkela, India","institution_ids":["https://openalex.org/I16292982"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101783559","display_name":"Banshidhar Majhi","orcid":"https://orcid.org/0000-0002-2843-1908"},"institutions":[{"id":"https://openalex.org/I16292982","display_name":"National Institute of Technology Rourkela","ror":"https://ror.org/011gmn932","country_code":"IN","type":"education","lineage":["https://openalex.org/I16292982"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Banshidhar Majhi","raw_affiliation_strings":["Department of Computer Science and Engineering, National Institute of Technology, Rourkela, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, National Institute of Technology, Rourkela, India","institution_ids":["https://openalex.org/I16292982"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5046512961"],"corresponding_institution_ids":["https://openalex.org/I16292982"],"apc_list":null,"apc_paid":null,"fwci":1.9604,"has_fulltext":false,"cited_by_count":29,"citation_normalized_percentile":{"value":0.86062884,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9998999834060669,"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":0.9998999834060669,"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/T12676","display_name":"Machine Learning and ELM","score":0.9873999953269958,"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9821000099182129,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7306959629058838},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.7286208271980286},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7130903005599976},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6617059707641602},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5924125909805298},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.5583265423774719},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.5344172120094299},{"id":"https://openalex.org/keywords/cad","display_name":"CAD","score":0.5304873585700989},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5008985996246338},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.5007569789886475},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.45817798376083374},{"id":"https://openalex.org/keywords/computer-aided-diagnosis","display_name":"Computer-aided diagnosis","score":0.45078742504119873},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.44155260920524597},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43304067850112915},{"id":"https://openalex.org/keywords/cohens-kappa","display_name":"Cohen's kappa","score":0.41834044456481934},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3205074071884155},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.16556131839752197},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.15282893180847168},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0776287317276001}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7306959629058838},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7286208271980286},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7130903005599976},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6617059707641602},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5924125909805298},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.5583265423774719},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.5344172120094299},{"id":"https://openalex.org/C194789388","wikidata":"https://www.wikidata.org/wiki/Q17855283","display_name":"CAD","level":2,"score":0.5304873585700989},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5008985996246338},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.5007569789886475},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.45817798376083374},{"id":"https://openalex.org/C2779549770","wikidata":"https://www.wikidata.org/wiki/Q1122413","display_name":"Computer-aided diagnosis","level":2,"score":0.45078742504119873},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.44155260920524597},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43304067850112915},{"id":"https://openalex.org/C163864269","wikidata":"https://www.wikidata.org/wiki/Q1107106","display_name":"Cohen's kappa","level":2,"score":0.41834044456481934},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3205074071884155},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.16556131839752197},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.15282893180847168},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0776287317276001},{"id":"https://openalex.org/C199639397","wikidata":"https://www.wikidata.org/wiki/Q1788588","display_name":"Engineering drawing","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ncvpripg.2015.7490068","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ncvpripg.2015.7490068","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Fifth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1601795611","https://openalex.org/W1903033156","https://openalex.org/W1974314515","https://openalex.org/W2016291052","https://openalex.org/W2017896827","https://openalex.org/W2038344945","https://openalex.org/W2050729568","https://openalex.org/W2075710390","https://openalex.org/W2083504715","https://openalex.org/W2090221122","https://openalex.org/W2098765040","https://openalex.org/W2115755118","https://openalex.org/W2153567216","https://openalex.org/W2911964244"],"related_works":["https://openalex.org/W4402452563","https://openalex.org/W2250488071","https://openalex.org/W2356150353","https://openalex.org/W2018643641","https://openalex.org/W2380744779","https://openalex.org/W2967867994","https://openalex.org/W2469878540","https://openalex.org/W4205690918","https://openalex.org/W2006362812","https://openalex.org/W1594962745"],"abstract_inverted_index":{"Development":[0],"of":[1,9,24,67,93,113,126,135,146,162,169],"computer-aided":[2],"diagnosis":[3],"(CAD)":[4],"systems":[5],"for":[6,42,123],"early":[7],"detection":[8],"the":[10,31,62,68,85,90,98,104,124,127,132,136,147,151],"pathological":[11,107],"brain":[12,43],"is":[13,49,121,142,154],"essential":[14],"to":[15,29,58,83,97,102,156],"save":[16],"medical":[17],"resources.":[18],"In":[19,34],"recent":[20],"years,":[21],"a":[22,37],"variety":[23],"techniques":[25,159],"have":[26,70],"been":[27,71],"proposed":[28,128,152],"upgrade":[30],"system's":[32],"performance.":[33],"this":[35],"paper,":[36],"new":[38],"automatic":[39],"CAD":[40],"system":[41],"magnetic":[44],"resonance":[45],"(MR)":[46],"image":[47],"classification":[48,163],"proposed.":[50],"The":[51,65,144],"method":[52],"utilizes":[53],"two-dimensional":[54],"discrete":[55],"wavelet":[56],"transform":[57],"extract":[59],"features":[60,69,94],"from":[61],"MR":[63],"images.":[64],"dimension":[66],"reduced":[72,91,167],"using":[73],"principal":[74],"component":[75],"analysis":[76,81],"(PCA)":[77],"and":[78,118],"linear":[79],"discriminant":[80],"(LDA),":[82],"obtain":[84],"more":[86],"significant":[87],"features.":[88,170],"Finally,":[89],"set":[92],"are":[95],"applied":[96],"random":[99],"forests":[100],"classifier":[101],"determine":[103],"normal":[105,117],"or":[106],"brain.":[108],"A":[109],"standard":[110],"dataset,":[111],"Dataset-255":[112],"255":[114],"images":[115],"(35":[116],"220":[119],"pathological)":[120],"used":[122],"validation":[125],"scheme.":[129],"To":[130],"improve":[131],"generalization":[133],"capability":[134],"scheme,":[137],"5-fold":[138],"stratified":[139],"cross-validation":[140],"procedure":[141],"utilized.":[143],"results":[145],"experiments":[148],"reveal":[149],"that":[150],"scheme":[153],"superior":[155],"other":[157],"state-of-the-art":[158],"in":[160],"terms":[161],"accuracy":[164],"with":[165],"substantially":[166],"number":[168]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}