{"id":"https://openalex.org/W2918366145","doi":"https://doi.org/10.1145/3297156.3297251","title":"Chest X-Ray Analysis of Tuberculosis by Convolutional Neural Networks with Affine Transforms","display_name":"Chest X-Ray Analysis of Tuberculosis by Convolutional Neural Networks with Affine Transforms","publication_year":2018,"publication_date":"2018-12-08","ids":{"openalex":"https://openalex.org/W2918366145","doi":"https://doi.org/10.1145/3297156.3297251","mag":"2918366145"},"language":"en","primary_location":{"id":"doi:10.1145/3297156.3297251","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3297156.3297251","pdf_url":null,"source":{"id":"https://openalex.org/S4306523626","display_name":"Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence","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/A5057144952","display_name":"Tawansongsang Karnkawinpong","orcid":null},"institutions":[{"id":"https://openalex.org/I158708052","display_name":"Chulalongkorn University","ror":"https://ror.org/028wp3y58","country_code":"TH","type":"education","lineage":["https://openalex.org/I158708052"]}],"countries":["TH"],"is_corresponding":true,"raw_author_name":"Tawansongsang Karnkawinpong","raw_affiliation_strings":["Department of Computer Engineering, Chulalongkorn University, Bangkok, Thailand"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Chulalongkorn University, Bangkok, Thailand","institution_ids":["https://openalex.org/I158708052"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034606101","display_name":"Yachai Limpiyakorn","orcid":"https://orcid.org/0000-0002-9370-5426"},"institutions":[{"id":"https://openalex.org/I158708052","display_name":"Chulalongkorn University","ror":"https://ror.org/028wp3y58","country_code":"TH","type":"education","lineage":["https://openalex.org/I158708052"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Yachai Limpiyakorn","raw_affiliation_strings":["Department of Computer Engineering, Chulalongkorn University, Bangkok, Thailand"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Chulalongkorn University, Bangkok, Thailand","institution_ids":["https://openalex.org/I158708052"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5057144952"],"corresponding_institution_ids":["https://openalex.org/I158708052"],"apc_list":null,"apc_paid":null,"fwci":1.5137,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.82246377,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"90","last_page":"93"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T10862","display_name":"AI in cancer detection","score":0.9793000221252441,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.876114010810852},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7942616939544678},{"id":"https://openalex.org/keywords/affine-transformation","display_name":"Affine transformation","score":0.7321396470069885},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7084105610847473},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6331398487091064},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5789185762405396},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5748616456985474},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.5090277194976807},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.49842333793640137},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.47198420763015747},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.39750438928604126},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3755130171775818},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1278429627418518}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.876114010810852},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7942616939544678},{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.7321396470069885},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7084105610847473},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6331398487091064},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5789185762405396},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5748616456985474},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.5090277194976807},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.49842333793640137},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.47198420763015747},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.39750438928604126},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3755130171775818},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1278429627418518},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3297156.3297251","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3297156.3297251","pdf_url":null,"source":{"id":"https://openalex.org/S4306523626","display_name":"Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W1836465849","https://openalex.org/W2097117768","https://openalex.org/W2163605009","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2310042802","https://openalex.org/W2508821345","https://openalex.org/W2531409750","https://openalex.org/W2774788879","https://openalex.org/W2775145835","https://openalex.org/W2789440170","https://openalex.org/W2792454083","https://openalex.org/W2794167658","https://openalex.org/W2925085025","https://openalex.org/W2949117887","https://openalex.org/W2963703618","https://openalex.org/W3104809143","https://openalex.org/W4246062521","https://openalex.org/W4253125535","https://openalex.org/W4301045096","https://openalex.org/W6600960895","https://openalex.org/W6601760687","https://openalex.org/W6631190155","https://openalex.org/W6819060087"],"related_works":["https://openalex.org/W2952813363","https://openalex.org/W2911497689","https://openalex.org/W4360783045","https://openalex.org/W4323287533","https://openalex.org/W4360994352","https://openalex.org/W2963346891","https://openalex.org/W2770149305","https://openalex.org/W2972076240","https://openalex.org/W3167930666","https://openalex.org/W3014952856"],"abstract_inverted_index":{"Applying":[0],"deep":[1],"learning":[2],"techniques":[3],"for":[4,30],"classification":[5,32],"of":[6,25,40,49,90],"medical":[7],"images":[8,82],"has":[9],"seen":[10],"considerable":[11],"growth":[12],"in":[13,46,66],"recent":[14],"years.":[15],"Among":[16],"several,":[17],"Convolutional":[18],"Neural":[19],"Net-works":[20],"(CNNs)":[21],"are":[22],"a":[23],"class":[24],"powerful":[26],"models":[27,111],"well":[28],"known":[29],"image":[31],"and":[33,58,101],"segmentation.":[34],"This":[35],"research":[36],"introduces":[37],"the":[38,77,91,97,109],"concept":[39],"computer-aided":[41],"diagnosis":[42,48],"that":[43,106],"could":[44],"help":[45],"early":[47],"Tuberculosis":[50],"infection.":[51],"The":[52,88,103],"three":[53,92],"CNN":[54],"architectures:":[55],"AlexNet,":[56],"VGG-16":[57],"CapsNet,":[59],"were":[60],"customized":[61],"to":[62,75],"classify":[63],"tuberculosis":[64],"lesions":[65],"CXR":[67,81],"images.":[68,115],"Data":[69],"augmentation":[70],"with":[71,96],"rotating":[72],"was":[73,94],"used":[74],"mimic":[76],"real":[78],"world":[79],"as":[80],"may":[83],"not":[84],"be":[85],"precisely":[86],"vertical.":[87],"performance":[89],"classifiers":[93],"evaluated":[95],"measures:":[98],"accuracy,":[99],"sensitivity":[100],"specificity.":[102],"result":[104],"showed":[105],"CapsNet":[107],"outperformed":[108],"other":[110],"when":[112],"predicting":[113],"affined":[114]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":3}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}
