{"id":"https://openalex.org/W2956162846","doi":"https://doi.org/10.1109/isbi.2019.8759324","title":"High Accuracy Patch-Level Classification of Wireless Capsule Endoscopy Images Using a Convolutional Neural Network","display_name":"High Accuracy Patch-Level Classification of Wireless Capsule Endoscopy Images Using a Convolutional Neural Network","publication_year":2019,"publication_date":"2019-04-01","ids":{"openalex":"https://openalex.org/W2956162846","doi":"https://doi.org/10.1109/isbi.2019.8759324","mag":"2956162846"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2019.8759324","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2019.8759324","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)","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/A5048273558","display_name":"Vinu Sankar Sadasivan","orcid":null},"institutions":[{"id":"https://openalex.org/I27674431","display_name":"Indian Institute of Technology Gandhinagar","ror":"https://ror.org/0036p5w23","country_code":"IN","type":"education","lineage":["https://openalex.org/I27674431"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vinu Sankar Sadasivan","raw_affiliation_strings":["Department of Computer Science and Engineering, Indian Institute of Technology, Gandhinagar, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Indian Institute of Technology, Gandhinagar, India","institution_ids":["https://openalex.org/I27674431"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005652970","display_name":"Chandra Sekhar Seelamantula","orcid":"https://orcid.org/0000-0001-9049-1912"},"institutions":[{"id":"https://openalex.org/I59270414","display_name":"Indian Institute of Science Bangalore","ror":"https://ror.org/04dese585","country_code":"IN","type":"education","lineage":["https://openalex.org/I59270414"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Chandra Sekhar Seelamantula","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Science, Bangalore, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Science, Bangalore, India","institution_ids":["https://openalex.org/I59270414"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":11.5723,"has_fulltext":true,"cited_by_count":18,"citation_normalized_percentile":{"value":0.99173554,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"96","last_page":"99"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11378","display_name":"Gastrointestinal Bleeding Diagnosis and Treatment","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2715","display_name":"Gastroenterology"},"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/T11378","display_name":"Gastrointestinal Bleeding Diagnosis and Treatment","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2715","display_name":"Gastroenterology"},"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/T10696","display_name":"Gastric Cancer Management and Outcomes","score":0.9139000177383423,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/capsule-endoscopy","display_name":"Capsule endoscopy","score":0.8794413805007935},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8368150591850281},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7814598083496094},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7459239959716797},{"id":"https://openalex.org/keywords/abnormality","display_name":"Abnormality","score":0.6369271278381348},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6160305142402649},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5385905504226685},{"id":"https://openalex.org/keywords/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.5053611397743225},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4931139647960663},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45264557003974915},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4324891269207001},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.41822928190231323},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.1632334291934967},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.11820366978645325},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.09371376037597656},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08134829998016357}],"concepts":[{"id":"https://openalex.org/C2777333622","wikidata":"https://www.wikidata.org/wiki/Q116753","display_name":"Capsule endoscopy","level":2,"score":0.8794413805007935},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8368150591850281},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7814598083496094},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7459239959716797},{"id":"https://openalex.org/C50965678","wikidata":"https://www.wikidata.org/wiki/Q2724302","display_name":"Abnormality","level":2,"score":0.6369271278381348},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6160305142402649},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5385905504226685},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.5053611397743225},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4931139647960663},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45264557003974915},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4324891269207001},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.41822928190231323},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.1632334291934967},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11820366978645325},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.09371376037597656},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08134829998016357},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/isbi.2019.8759324","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2019.8759324","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)","raw_type":"proceedings-article"},{"id":"pmh:oai::78338","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306401702","display_name":"Universitas Pasundan institutional repositories & scientific journals (Universitas Pasundan)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210159629","host_organization_name":"Universitas Pasundan","host_organization_lineage":["https://openalex.org/I4210159629"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1582903324","https://openalex.org/W1650175677","https://openalex.org/W1980301542","https://openalex.org/W2029049224","https://openalex.org/W2147595228","https://openalex.org/W2155653793","https://openalex.org/W2163605009","https://openalex.org/W2533853894","https://openalex.org/W2691395254","https://openalex.org/W6657578410","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W4229921108","https://openalex.org/W2124653584","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3167935049","https://openalex.org/W3103566983","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Wireless":[0],"capsule":[1],"endoscopy":[2],"(WCE)":[3],"is":[4,90],"a":[5,26,32,55,66,80,125],"technology":[6],"used":[7,91],"to":[8,57,79,92,95],"record":[9],"colored":[10],"internal":[11],"images":[12,64,72],"of":[13,21,29,40,44,121],"the":[14,19,38,59,108],"gastrointestinal":[15],"(GI)":[16],"tract":[17],"for":[18],"purpose":[20],"medical":[22],"diagnosis.":[23],"It":[24],"transmits":[25],"large":[27],"number":[28],"frames":[30],"in":[31,62],"single":[33],"examination":[34],"cycle,":[35],"which":[36],"makes":[37],"process":[39],"analyzing":[41],"and":[42,48,77],"diagnosis":[43],"abnormalities":[45,104],"extremely":[46],"challenging":[47],"time-consuming.":[49],"In":[50],"this":[51],"paper,":[52],"we":[53],"propose":[54],"technique":[56],"automate":[58],"abnormality":[60],"detection":[61],"WCE":[63,71,109],"following":[65],"deep":[67,87],"learning":[68],"approach.":[69],"The":[70,101],"are":[73,105],"split":[74],"into":[75],"patches":[76,94,102],"input":[78],"convolutional":[81],"neural":[82,88],"network":[83,89],"(CNN).":[84],"A":[85],"trained":[86],"classify":[93],"be":[96],"either":[97],"malign":[98],"or":[99],"benign.":[100],"with":[103],"marked":[106],"on":[107,124],"image":[110],"output.":[111],"We":[112],"obtained":[113],"an":[114],"area":[115],"under":[116],"receiver-operating-characteristic":[117],"curve":[118],"(AUROC)":[119],"value":[120],"about":[122],"98.65%":[123],"publicly":[126],"available":[127],"test":[128],"data":[129],"containing":[130],"nine":[131],"abnormalities.":[132]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":4}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
