{"id":"https://openalex.org/W1571883788","doi":"https://doi.org/10.1109/isbi.2015.7163868","title":"Adjustable adaboost classifier and pyramid features for image-based cervical cancer diagnosis","display_name":"Adjustable adaboost classifier and pyramid features for image-based cervical cancer diagnosis","publication_year":2015,"publication_date":"2015-04-01","ids":{"openalex":"https://openalex.org/W1571883788","doi":"https://doi.org/10.1109/isbi.2015.7163868","mag":"1571883788"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2015.7163868","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2015.7163868","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)","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/A5100621909","display_name":"Tao Xu","orcid":"https://orcid.org/0000-0003-3705-4152"},"institutions":[{"id":"https://openalex.org/I186143895","display_name":"Lehigh University","ror":"https://ror.org/012afjb06","country_code":"US","type":"education","lineage":["https://openalex.org/I186143895"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tao Xu","raw_affiliation_strings":["Computer Science and Engineering Department, Lehigh University, Bethlehem, PA, USA","Computer Science & Engineering Department, Lehigh University, Bethlehem, PA, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering Department, Lehigh University, Bethlehem, PA, USA","institution_ids":["https://openalex.org/I186143895"]},{"raw_affiliation_string":"Computer Science & Engineering Department, Lehigh University, Bethlehem, PA, USA","institution_ids":["https://openalex.org/I186143895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100728159","display_name":"Edward Kim","orcid":"https://orcid.org/0000-0001-5345-3781"},"institutions":[{"id":"https://openalex.org/I7863295","display_name":"Villanova University","ror":"https://ror.org/02g7kd627","country_code":"US","type":"education","lineage":["https://openalex.org/I7863295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Edward Kim","raw_affiliation_strings":["Department of Computing Sciences, Villanova University, Villanova, PA, USA","[Department of Computing Sciences, Villanova University, Villanova, PA, USA]"],"affiliations":[{"raw_affiliation_string":"Department of Computing Sciences, Villanova University, Villanova, PA, USA","institution_ids":["https://openalex.org/I7863295"]},{"raw_affiliation_string":"[Department of Computing Sciences, Villanova University, Villanova, PA, USA]","institution_ids":["https://openalex.org/I7863295"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000467703","display_name":"Xiaolei Huang","orcid":"https://orcid.org/0000-0003-2338-6535"},"institutions":[{"id":"https://openalex.org/I186143895","display_name":"Lehigh University","ror":"https://ror.org/012afjb06","country_code":"US","type":"education","lineage":["https://openalex.org/I186143895"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaolei Huang","raw_affiliation_strings":["Computer Science and Engineering Department, Lehigh University, Bethlehem, PA, USA","Computer Science & Engineering Department, Lehigh University, Bethlehem, PA, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering Department, Lehigh University, Bethlehem, PA, USA","institution_ids":["https://openalex.org/I186143895"]},{"raw_affiliation_string":"Computer Science & Engineering Department, Lehigh University, Bethlehem, PA, USA","institution_ids":["https://openalex.org/I186143895"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100621909"],"corresponding_institution_ids":["https://openalex.org/I186143895"],"apc_list":null,"apc_paid":null,"fwci":0.5523,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.73167954,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"281","last_page":"285"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9932000041007996,"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":0.9932000041007996,"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":0.9901000261306763,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9814000129699707,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.791952908039093},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.7532288432121277},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7095422148704529},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6906550526618958},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.621464192867279},{"id":"https://openalex.org/keywords/local-binary-patterns","display_name":"Local binary patterns","score":0.577794075012207},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5700193047523499},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.512103796005249},{"id":"https://openalex.org/keywords/cervical-cancer","display_name":"Cervical cancer","score":0.5041607618331909},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.47507327795028687},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.45302411913871765},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4192492365837097},{"id":"https://openalex.org/keywords/histogram-of-oriented-gradients","display_name":"Histogram of oriented gradients","score":0.41388750076293945},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2318979799747467},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.1937328577041626},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16282284259796143},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1451314091682434}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.791952908039093},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.7532288432121277},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7095422148704529},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6906550526618958},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.621464192867279},{"id":"https://openalex.org/C87335442","wikidata":"https://www.wikidata.org/wiki/Q2494345","display_name":"Local binary patterns","level":4,"score":0.577794075012207},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5700193047523499},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.512103796005249},{"id":"https://openalex.org/C2778220009","wikidata":"https://www.wikidata.org/wiki/Q160105","display_name":"Cervical cancer","level":3,"score":0.5041607618331909},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.47507327795028687},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.45302411913871765},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4192492365837097},{"id":"https://openalex.org/C17426736","wikidata":"https://www.wikidata.org/wiki/Q419918","display_name":"Histogram of oriented gradients","level":4,"score":0.41388750076293945},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2318979799747467},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.1937328577041626},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16282284259796143},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1451314091682434},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2015.7163868","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2015.7163868","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W35451206","https://openalex.org/W325298687","https://openalex.org/W1975729954","https://openalex.org/W1978090225","https://openalex.org/W1979319218","https://openalex.org/W1998234672","https://openalex.org/W2039051707","https://openalex.org/W2052733478","https://openalex.org/W2072564388","https://openalex.org/W2113635748","https://openalex.org/W2113833709","https://openalex.org/W2113874502","https://openalex.org/W2133263698","https://openalex.org/W2143391725","https://openalex.org/W2147541126","https://openalex.org/W2154683974","https://openalex.org/W2163352848","https://openalex.org/W6611250921","https://openalex.org/W6645182988","https://openalex.org/W6663820137","https://openalex.org/W6676855097"],"related_works":["https://openalex.org/W4224879220","https://openalex.org/W2348780717","https://openalex.org/W2046724945","https://openalex.org/W2999130902","https://openalex.org/W3211626993","https://openalex.org/W2507467930","https://openalex.org/W4281681299","https://openalex.org/W4315797013","https://openalex.org/W2904398182","https://openalex.org/W2347245106"],"abstract_inverted_index":{"Cervical":[0],"cancer":[1,9,18],"is":[2,38,108,133],"the":[3,25,54,64,76,126],"third":[4],"most":[5],"common":[6],"type":[7],"of":[8,16,24,67,128],"in":[10,20,40,112],"women":[11],"worldwide.":[12],"Most":[13],"death":[14],"cases":[15],"cervical":[17,55],"occur":[19],"less":[21],"developed":[22],"areas":[23],"world.":[26],"In":[27],"this":[28],"work,":[29],"we":[30,45,74],"develop":[31],"an":[32,60],"automated":[33],"and":[34,83,119,145],"low-cost":[35],"method":[36,132],"that":[37],"applicable":[39],"those":[41],"low-resource":[42],"regions.":[43],"First,":[44],"propose":[46],"a":[47,85],"more":[48],"distinctive":[49],"multi-feature":[50],"descriptor":[51,62],"for":[52,110],"encoding":[53],"image":[56],"information":[57],"by":[58],"enhancing":[59],"existing":[61,140],"with":[63],"pyramid":[65],"histogram":[66],"local":[68],"binary":[69,86],"pattern":[70],"(PLBP)":[71],"feature.":[72],"Second,":[73],"apply":[75],"AdaBoost":[77,98],"algorithm":[78],"to":[79,88,103,124,135],"perform":[80],"feature":[81],"selection,":[82],"train":[84],"classifier":[87,99],"differentiate":[89],"high-risk":[90],"patient":[91,95],"visits":[92],"from":[93],"low-risk":[94],"visits.":[96],"Our":[97,131],"can":[100],"be":[101],"adjusted":[102],"achieve":[104,136],"high":[105],"specificity,":[106],"which":[107],"necessary":[109],"use":[111],"clinical":[113],"practice.":[114],"Experiments":[115],"on":[116,150],"both":[117],"balanced":[118],"imbalanced":[120],"datasets":[121],"are":[122],"conducted":[123],"evaluate":[125],"effectiveness":[127],"our":[129],"method.":[130],"shown":[134],"better":[137],"performance":[138],"than":[139],"image-based":[141],"CIN":[142],"classification":[143],"systems":[144],"also":[146],"outperform":[147],"human":[148],"interpretations":[149],"various":[151],"screening":[152],"tests.":[153]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
