{"id":"https://openalex.org/W3026969527","doi":"https://doi.org/10.1109/isbi45749.2020.9098587","title":"Region of Interest Identification for Cervical Cancer Images","display_name":"Region of Interest Identification for Cervical Cancer Images","publication_year":2020,"publication_date":"2020-04-01","ids":{"openalex":"https://openalex.org/W3026969527","doi":"https://doi.org/10.1109/isbi45749.2020.9098587","mag":"3026969527"},"language":"en","primary_location":{"id":"doi:10.1109/isbi45749.2020.9098587","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi45749.2020.9098587","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5046755750","display_name":"Manish Gupta","orcid":"https://orcid.org/0000-0002-2843-3110"},"institutions":[{"id":"https://openalex.org/I4210162141","display_name":"Microsoft (India)","ror":"https://ror.org/04ww0w091","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210162141"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Manish Gupta","raw_affiliation_strings":["Microsoft, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft, India","institution_ids":["https://openalex.org/I4210162141"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021864126","display_name":"Chetna Das","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162141","display_name":"Microsoft (India)","ror":"https://ror.org/04ww0w091","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210162141"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Chetna Das","raw_affiliation_strings":["Microsoft, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft, India","institution_ids":["https://openalex.org/I4210162141"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100605963","display_name":"Arnab Roy","orcid":"https://orcid.org/0000-0002-3284-7076"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Arnab Roy","raw_affiliation_strings":["SRL Diagnostics, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SRL Diagnostics, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048725802","display_name":"Prashant Gupta","orcid":"https://orcid.org/0000-0003-4220-1954"},"institutions":[{"id":"https://openalex.org/I4210162141","display_name":"Microsoft (India)","ror":"https://ror.org/04ww0w091","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210162141"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Prashant Gupta","raw_affiliation_strings":["Microsoft, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft, India","institution_ids":["https://openalex.org/I4210162141"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042941365","display_name":"G. Radhakrishna Pillai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"G. Radhakrishna Pillai","raw_affiliation_strings":["SRL Diagnostics, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SRL Diagnostics, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064624742","display_name":"Kamlakar Patole","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kamlakar Patole","raw_affiliation_strings":["SRL Diagnostics, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SRL Diagnostics, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1293","last_page":"1296"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9998000264167786,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9908999800682068,"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/T10146","display_name":"Cervical Cancer and HPV Research","score":0.9897000193595886,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7665749788284302},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6589069962501526},{"id":"https://openalex.org/keywords/cervical-cancer","display_name":"Cervical cancer","score":0.64969801902771},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6192684769630432},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5559445023536682},{"id":"https://openalex.org/keywords/region-of-interest","display_name":"Region of interest","score":0.4868621230125427},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.476068913936615},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.4575180113315582},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.448320597410202},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.4455743134021759},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4395561218261719},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35847389698028564},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.3247086703777313},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3223763704299927},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.2612486481666565},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.0925336480140686}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7665749788284302},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6589069962501526},{"id":"https://openalex.org/C2778220009","wikidata":"https://www.wikidata.org/wiki/Q160105","display_name":"Cervical cancer","level":3,"score":0.64969801902771},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6192684769630432},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5559445023536682},{"id":"https://openalex.org/C19609008","wikidata":"https://www.wikidata.org/wiki/Q2138203","display_name":"Region of interest","level":2,"score":0.4868621230125427},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.476068913936615},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.4575180113315582},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.448320597410202},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.4455743134021759},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4395561218261719},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35847389698028564},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3247086703777313},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3223763704299927},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.2612486481666565},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0925336480140686},{"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/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi45749.2020.9098587","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi45749.2020.9098587","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.5,"display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1582640985","https://openalex.org/W1686810756","https://openalex.org/W2051765910","https://openalex.org/W2133765716","https://openalex.org/W2140839650","https://openalex.org/W2504150216","https://openalex.org/W2592929672","https://openalex.org/W2594262533","https://openalex.org/W2611650229","https://openalex.org/W2616720730","https://openalex.org/W2962858109","https://openalex.org/W2963446712","https://openalex.org/W3101156210","https://openalex.org/W3102737931","https://openalex.org/W6734900802"],"related_works":["https://openalex.org/W2361861616","https://openalex.org/W2263699433","https://openalex.org/W2377979023","https://openalex.org/W2218034408","https://openalex.org/W2392921965","https://openalex.org/W2358755282","https://openalex.org/W2625833328","https://openalex.org/W1533177136","https://openalex.org/W4380994516","https://openalex.org/W2251519152"],"abstract_inverted_index":{"Every":[0],"two":[1],"minutes":[2],"one":[3],"woman":[4],"dies":[5],"of":[6,13,48,65,108,130,139,142,147,169],"cervical":[7,52,84],"cancer":[8],"globally,":[9],"due":[10],"to":[11,41,45,119],"lack":[12,64],"sufficient":[14],"screening.":[15],"Given":[16],"a":[17,25,30,91,98,137,150,166],"whole":[18],"slide":[19,28],"image":[20,57],"(WSI)":[21],"obtained":[22],"by":[23,117],"scanning":[24],"microscope":[26],"glass":[27],"for":[29,115,149,154],"Liquid":[31],"Based":[32],"Cytology":[33],"(LBC)":[34],"based":[35,104],"Pap":[36],"test,":[37],"our":[38],"goal":[39],"is":[40,103],"assist":[42],"the":[43,131],"pathologist":[44],"determine":[46],"presence":[47],"precancerous":[49],"or":[50],"cancerous":[51],"anomalies.":[53],"Inter-annotator":[54],"variation,":[55],"large":[56],"sizes,":[58],"data":[59],"imbalance,":[60],"stain":[61],"variations,":[62],"and":[63,83],"good":[66],"annotation":[67],"tools":[68],"make":[69],"this":[70],"problem":[71],"challenging.":[72],"Existing":[73],"related":[74],"work":[75],"has":[76],"focused":[77],"on":[78,105,110],"sub-problems":[79],"like":[80],"cell":[81,85],"segmentation":[82],"classification":[86,160],"but":[87],"does":[88],"not":[89],"provide":[90],"practically":[92],"feasible":[93],"holistic":[94],"solution.":[95],"We":[96,122],"propose":[97],"practical":[99],"system":[100,164],"architecture":[101],"which":[102],"displaying":[106],"regions":[107,141],"interest":[109,143],"WSIs":[111],"containing":[112],"potential":[113],"anomaly":[114],"review":[116],"pathologists":[118],"increase":[120],"productivity.":[121],"build":[123],"multiple":[124],"deep":[125],"learning":[126],"classifiers":[127],"as":[128,156,158],"part":[129],"proposed":[132],"architecture.":[133],"Our":[134,162],"experiments":[135],"with":[136],"dataset":[138,152],"~19000":[140],"provides":[144,165],"an":[145],"accuracy":[146,168],"~89%":[148],"balanced":[151],"both":[153],"binary":[155],"well":[157],"6-class":[159],"settings.":[161],"deployed":[163],"top-5":[167],"~94%.":[170]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
