{"id":"https://openalex.org/W2165784799","doi":"https://doi.org/10.1109/isbi.2008.4541039","title":"Combining multiple 2&amp;#x03BD;-SVM classifiers for tissue segmentation","display_name":"Combining multiple 2&amp;#x03BD;-SVM classifiers for tissue segmentation","publication_year":2008,"publication_date":"2008-05-01","ids":{"openalex":"https://openalex.org/W2165784799","doi":"https://doi.org/10.1109/isbi.2008.4541039","mag":"2165784799"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2008.4541039","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2008.4541039","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","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/A5038884712","display_name":"Yusuf Artan","orcid":null},"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":"Yusuf Artan","raw_affiliation_strings":["Department of Electrical Engineering, Lehigh University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Lehigh University, USA","institution_ids":["https://openalex.org/I186143895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063975216","display_name":"Xiaolei Huang","orcid":"https://orcid.org/0000-0002-4073-4848"},"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":["Department of Computer Science and Engineering, Lehigh University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Lehigh University, USA","institution_ids":["https://openalex.org/I186143895"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I186143895"],"apc_list":null,"apc_paid":null,"fwci":3.1953,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.92766487,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"488","last_page":"491"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9948999881744385,"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":0.9948999881744385,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9944999814033508,"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":0.9939000010490417,"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/support-vector-machine","display_name":"Support vector machine","score":0.7900852560997009},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.731683611869812},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.666421115398407},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6648027896881104},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6432187557220459},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6352025270462036},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5736389756202698},{"id":"https://openalex.org/keywords/classification-scheme","display_name":"Classification scheme","score":0.4994997978210449},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.46813687682151794},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.333890825510025},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.19649654626846313}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7900852560997009},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.731683611869812},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.666421115398407},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6648027896881104},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6432187557220459},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6352025270462036},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5736389756202698},{"id":"https://openalex.org/C13460635","wikidata":"https://www.wikidata.org/wiki/Q85753676","display_name":"Classification scheme","level":2,"score":0.4994997978210449},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.46813687682151794},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.333890825510025},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.19649654626846313}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2008.4541039","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2008.4541039","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.6200000047683716,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337351","display_name":"National Cancer Institute","ror":"https://ror.org/040gcmg81"},{"id":"https://openalex.org/F4320337372","display_name":"U.S. National Library of Medicine","ror":"https://ror.org/0060t0j89"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1585450072","https://openalex.org/W1936866406","https://openalex.org/W1975729954","https://openalex.org/W1988642394","https://openalex.org/W1993456370","https://openalex.org/W2038952578","https://openalex.org/W2077033818","https://openalex.org/W2137346077","https://openalex.org/W2148347694","https://openalex.org/W2148603752","https://openalex.org/W2163599171","https://openalex.org/W3133603318","https://openalex.org/W6635116231"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W2104657898","https://openalex.org/W1948992892","https://openalex.org/W1886884218","https://openalex.org/W1910826599","https://openalex.org/W2005234362","https://openalex.org/W1997235926","https://openalex.org/W3134034502","https://openalex.org/W2148260872"],"abstract_inverted_index":{"In":[0],"image":[1,104],"classification":[2,54,62,105,154],"problems,":[3],"especially":[4],"those":[5],"involving":[6],"tumor":[7],"or":[8],"precancerous":[9],"lesion,":[10],"we":[11,78],"are":[12,79],"usually":[13],"faced":[14],"with":[15],"the":[16,20,35,39,87,95,133,142,148],"situation":[17],"in":[18,26,38,52,117,122],"which":[19],"cost":[21,48],"of":[22,34,97,126,135,141],"mistakenly":[23],"classifying":[24],"samples":[25],"one":[27],"class":[28,88],"is":[29,44,90,132],"much":[30],"higher":[31,84],"than":[32],"that":[33,89],"opposite":[36],"mistake":[37],"other":[40],"class.":[41],"Therefore":[42],"it":[43],"essential":[45],"to":[46,64,68,81,86],"include":[47],"information":[49],"about":[50],"classes":[51],"our":[53,98,159],"methods.":[55],"This":[56],"paper":[57],"applies":[58],"a":[59,83,123,136],"cost-sensitive":[60,100],"2\u03bd-SVM":[61],"scheme":[63,139,151],"cervical":[65],"cancer":[66],"images":[67,121],"separate":[69],"diseased":[70],"regions":[71,116],"from":[72],"healthy":[73],"tissue.":[74],"Using":[75,147],"this":[76],"method,":[77],"able":[80],"specify":[82],"weight":[85],"deemed":[91],"more":[92],"important.":[93],"To":[94],"best":[96],"knowledge,":[99],"SVM":[101],"based":[102],"medical":[103],"has":[106],"not":[107],"been":[108],"done":[109],"before.":[110],"We":[111],"specifically":[112],"target":[113],"segmenting":[114],"disease":[115],"digitized":[118],"uterine":[119],"cervix":[120],"NCI/NLM":[124],"archive":[125],"60,000":[127],"images.":[128],"Our":[129],"second":[130],"contribution":[131],"introduction":[134],"multiple":[137,149],"classifier":[138,145,150],"instead":[140],"traditional":[143],"single":[144],"model.":[146],"improves":[152],"significantly":[153],"accuracy":[155],"as":[156],"demonstrated":[157],"by":[158],"experiments.":[160]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
