{"id":"https://openalex.org/W1586903776","doi":"https://doi.org/10.1109/isbi.2015.7163821","title":"Automatic polyp detection in colonoscopy videos using an ensemble of convolutional neural networks","display_name":"Automatic polyp detection in colonoscopy videos using an ensemble of convolutional neural networks","publication_year":2015,"publication_date":"2015-04-01","ids":{"openalex":"https://openalex.org/W1586903776","doi":"https://doi.org/10.1109/isbi.2015.7163821","mag":"1586903776"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2015.7163821","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2015.7163821","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":"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/A5011019569","display_name":"Nima Tajbakhsh","orcid":"https://orcid.org/0000-0001-8614-4811"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nima Tajbakhsh","raw_affiliation_strings":["Department of Biomedical Informatics, Arizona State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Informatics, Arizona State University","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113882105","display_name":"Suryakanth Gurudu","orcid":null},"institutions":[{"id":"https://openalex.org/I1330342723","display_name":"Mayo Clinic","ror":"https://ror.org/02qp3tb03","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1330342723"]},{"id":"https://openalex.org/I4210125099","display_name":"Mayo Clinic in Arizona","ror":"https://ror.org/03jp40720","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1330342723","https://openalex.org/I4210125099"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Suryakanth R. Gurudu","raw_affiliation_strings":["Division of Gastroenterology and Hepatology, Mayo Clinic","[Division of Gastroenterology and Hepatology, Mayo Clinic]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Gastroenterology and Hepatology, Mayo Clinic","institution_ids":["https://openalex.org/I4210125099"]},{"raw_affiliation_string":"[Division of Gastroenterology and Hepatology, Mayo Clinic]","institution_ids":["https://openalex.org/I1330342723"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040454904","display_name":"Jianming Liang","orcid":"https://orcid.org/0000-0001-5486-1613"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianming Liang","raw_affiliation_strings":["Department of Biomedical Informatics, Arizona State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Informatics, Arizona State University","institution_ids":["https://openalex.org/I55732556"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":57.3143,"has_fulltext":false,"cited_by_count":159,"citation_normalized_percentile":{"value":0.99800399,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"79","last_page":"83"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10552","display_name":"Colorectal Cancer Screening and Detection","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10552","display_name":"Colorectal Cancer Screening and Detection","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9714000225067139,"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":0.9569000005722046,"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/computer-science","display_name":"Computer science","score":0.7908514738082886},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7643262147903442},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.7388115525245667},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7246225476264954},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5908933281898499},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4674834609031677},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.46666043996810913},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4628232419490814},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.44710901379585266},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.355191707611084}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7908514738082886},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7643262147903442},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.7388115525245667},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7246225476264954},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5908933281898499},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4674834609031677},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.46666043996810913},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4628232419490814},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.44710901379585266},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.355191707611084},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2015.7163821","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2015.7163821","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":[{"score":0.5299999713897705,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306143","display_name":"Mayo Clinic","ror":"https://ror.org/02qp3tb03"},{"id":"https://openalex.org/F4320309835","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W116236279","https://openalex.org/W199419312","https://openalex.org/W1915761309","https://openalex.org/W2001557487","https://openalex.org/W2034269173","https://openalex.org/W2054367831","https://openalex.org/W2057098199","https://openalex.org/W2093217571","https://openalex.org/W2094155432","https://openalex.org/W2106904071","https://openalex.org/W2111116696","https://openalex.org/W2113889984","https://openalex.org/W2118772243","https://openalex.org/W2140753590","https://openalex.org/W2141125852","https://openalex.org/W2163605009","https://openalex.org/W2164733507","https://openalex.org/W6608194093","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W1557094818","https://openalex.org/W2183246718","https://openalex.org/W2099261052","https://openalex.org/W3209204065","https://openalex.org/W1755711892","https://openalex.org/W2160907113","https://openalex.org/W2070813941","https://openalex.org/W2964954556","https://openalex.org/W2969228573","https://openalex.org/W2963690996"],"abstract_inverted_index":{"Computer-aided":[0],"polyp":[1,22,36,56,73,77,132,169,184],"detection":[2,23,37,170,194],"in":[3,66,88,96,149,185],"colonoscopy":[4],"videos":[5],"has":[6],"been":[7],"the":[8,14,97,100,113,129,140,144,176,179,186,189],"subject":[9],"of":[10,55,81,91,99,122,146,182,191],"research":[11],"for":[12],"over":[13,139],"past":[15],"decade.":[16],"However,":[17],"despite":[18],"significant":[19],"advances,":[20],"automatic":[21],"is":[24,128,173],"still":[25],"an":[26],"unsolved":[27],"problem.":[28],"In":[29,154],"this":[30],"paper,":[31],"we":[32,156],"propose":[33,157],"a":[34,41,53,70,76,79,135,158,183],"new":[35,159,165],"method":[38,51,166],"based":[39,118],"on":[40,119],"unique":[42],"3-way":[43],"image":[44],"presentation":[45],"and":[46,63,102],"convolutional":[47],"neural":[48,83],"networks.":[49],"Our":[50,115],"learns":[52],"variety":[54],"features":[57,92],"such":[58],"as":[59,175],"color,":[60],"texture,":[61],"shape,":[62],"temporal":[64],"information":[65],"multiple":[67],"scales,":[68],"enabling":[69],"more":[71],"accurate":[72],"localization.":[74],"Given":[75],"candidate,":[78],"set":[80],"convolution":[82],"networks":[84],"-":[85,93],"each":[86],"specialized":[87],"one":[89],"type":[90],"are":[94,106],"applied":[95],"vicinity":[98],"candidate":[101],"then":[103],"their":[104],"results":[105,117],"aggregated":[107],"to":[108,125,188],"either":[109],"accept":[110],"or":[111],"reject":[112],"candidate.":[114],"experimental":[116],"our":[120,126,164,196],"collection":[121],"videos,":[123],"which":[124,172],"knowledge":[127],"largest":[130],"annotated":[131],"database,":[133],"shows":[134],"remarkable":[136],"performance":[137,160],"improvement":[138],"state-of-the-art,":[141],"significantly":[142,167],"reducing":[143],"number":[145],"false":[147],"positives":[148],"nearly":[150],"all":[151],"operating":[152],"points.":[153],"addition,":[155],"curve,":[161],"demonstrating":[162],"that":[163],"decreases":[168],"latency,":[171],"defined":[174],"time":[177,190],"from":[178],"first":[180,193],"appearance":[181],"video":[187],"its":[192],"by":[195],"method.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":20},{"year":2020,"cited_by_count":22},{"year":2019,"cited_by_count":24},{"year":2018,"cited_by_count":19},{"year":2017,"cited_by_count":13},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":2}],"updated_date":"2026-08-15T07:11:24.734988","created_date":"2025-10-10T00:00:00"}
