{"id":"https://openalex.org/W3022637981","doi":"https://doi.org/10.1145/3293353.3293408","title":"Jointly Learning Convolutional Representations to Compress Radiological Images and Classify Thoracic Diseases in the Compressed Domain","display_name":"Jointly Learning Convolutional Representations to Compress Radiological Images and Classify Thoracic Diseases in the Compressed Domain","publication_year":2018,"publication_date":"2018-12-18","ids":{"openalex":"https://openalex.org/W3022637981","doi":"https://doi.org/10.1145/3293353.3293408","mag":"3022637981"},"language":"en","primary_location":{"id":"doi:10.1145/3293353.3293408","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3293353.3293408","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 11th Indian Conference on Computer Vision, Graphics and Image Processing","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/A5082363791","display_name":"Ekagra Ranjan","orcid":null},"institutions":[{"id":"https://openalex.org/I1317621060","display_name":"Indian Institute of Technology Guwahati","ror":"https://ror.org/0022nd079","country_code":"IN","type":"education","lineage":["https://openalex.org/I1317621060"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Ekagra Ranjan","raw_affiliation_strings":["Indian Institute of Technology, Guwahati, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Guwahati, India","institution_ids":["https://openalex.org/I1317621060"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110796601","display_name":"Soumava Paul","orcid":null},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Soumava Paul","raw_affiliation_strings":["Indian Institute of Technology, Kharagpur, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Kharagpur, India","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080234230","display_name":"Siddharth Kapoor","orcid":null},"institutions":[{"id":"https://openalex.org/I11880225","display_name":"National Institute of Technology Karnataka","ror":"https://ror.org/01hz4v948","country_code":"IN","type":"education","lineage":["https://openalex.org/I11880225"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Siddharth Kapoor","raw_affiliation_strings":["National Institute of Technology, Karnataka, India"],"affiliations":[{"raw_affiliation_string":"National Institute of Technology, Karnataka, India","institution_ids":["https://openalex.org/I11880225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017373839","display_name":"Aupendu Kar","orcid":"https://orcid.org/0000-0001-5696-5002"},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Aupendu Kar","raw_affiliation_strings":["Indian Institute of Technology, Kharagpur, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Kharagpur, India","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023217610","display_name":"Ramanathan Sethuraman","orcid":"https://orcid.org/0000-0002-0708-7669"},"institutions":[{"id":"https://openalex.org/I4210146682","display_name":"Intel (India)","ror":"https://ror.org/04f2n1245","country_code":"IN","type":"company","lineage":["https://openalex.org/I1343180700","https://openalex.org/I4210146682"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ramanathan Sethuraman","raw_affiliation_strings":["Intel Technology India Pvt. Ltd., Bangalore, India"],"affiliations":[{"raw_affiliation_string":"Intel Technology India Pvt. Ltd., Bangalore, India","institution_ids":["https://openalex.org/I4210146682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010986022","display_name":"Debdoot Sheet","orcid":"https://orcid.org/0000-0001-9046-149X"},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Debdoot Sheet","raw_affiliation_strings":["Indian Institute of Technology, Kharagpur, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Kharagpur, India","institution_ids":["https://openalex.org/I145894827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5082363791"],"corresponding_institution_ids":["https://openalex.org/I1317621060"],"apc_list":null,"apc_paid":null,"fwci":2.829,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.91443319,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9994000196456909,"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":0.9994000196456909,"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":0.9968000054359436,"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/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9955000281333923,"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/autoencoder","display_name":"Autoencoder","score":0.8223974704742432},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8050573468208313},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7988313436508179},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7408205270767212},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7224673628807068},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5982979536056519},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5936437845230103},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5427889823913574},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.495098739862442},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.41689518094062805},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3741321563720703},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06154739856719971}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8223974704742432},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8050573468208313},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7988313436508179},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7408205270767212},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7224673628807068},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5982979536056519},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5936437845230103},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5427889823913574},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.495098739862442},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41689518094062805},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3741321563720703},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06154739856719971},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3293353.3293408","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3293353.3293408","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 11th Indian Conference on Computer Vision, Graphics and Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1861492603","https://openalex.org/W1976526581","https://openalex.org/W2016053056","https://openalex.org/W2064675550","https://openalex.org/W2097117768","https://openalex.org/W2108598243","https://openalex.org/W2110798204","https://openalex.org/W2116064496","https://openalex.org/W2136922672","https://openalex.org/W2158698691","https://openalex.org/W2163605009","https://openalex.org/W2169488311","https://openalex.org/W2176412452","https://openalex.org/W2194775991","https://openalex.org/W2312404985","https://openalex.org/W2401520370","https://openalex.org/W2476548250","https://openalex.org/W2502390809","https://openalex.org/W2581082771","https://openalex.org/W2611650229","https://openalex.org/W2765312638","https://openalex.org/W2786052267","https://openalex.org/W2793854008","https://openalex.org/W2951261633","https://openalex.org/W2962708065","https://openalex.org/W2963446712","https://openalex.org/W3101156210","https://openalex.org/W3104258355","https://openalex.org/W4212774754","https://openalex.org/W4234552385"],"related_works":["https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W4392946183","https://openalex.org/W3088732000","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Deep":[0],"learning":[1,35],"models":[2,36],"trained":[3,121],"in":[4,14,70,172],"natural":[5],"images":[6,23,45,72,134],"are":[7,24,38,120],"commonly":[8],"used":[9,142],"for":[10,135],"different":[11,169],"classification":[12,92,136],"tasks":[13,119],"the":[15,58,65,98,101,108,118,126,143,166],"medical":[16,22,71],"domain.":[17],"Generally,":[18],"very":[19],"high":[20],"dimensional":[21],"down-sampled":[25],"by":[26],"using":[27,103,113,178],"interpolation":[28],"techniques":[29],"before":[30],"feeding":[31],"them":[32],"to":[33,57,96,128,150],"deep":[34],"that":[37],"ImageNet":[39,182],"compliant":[40],"and":[41,77,106,154,175],"accept":[42],"only":[43],"low-resolution":[44],"of":[46,60,100,147,168,184],"size":[47],"224":[48,50],"x":[49],"px.":[51],"This":[52,123],"popular":[53],"technique":[54],"may":[55],"lead":[56],"loss":[59],"key":[61],"information":[62],"thus":[63],"hampering":[64],"classification.":[66],"Significant":[67],"pathological":[68],"features":[69],"typically":[73],"being":[74],"small":[75],"sized":[76],"highly":[78],"affected.":[79],"To":[80],"combat":[81],"this":[82,152,173],"problem,":[83],"we":[84,162],"introduce":[85],"a":[86],"convolutional":[87],"neural":[88],"network":[89],"(CNN)":[90],"based":[91],"approach":[93,153],"which":[94],"learns":[95],"reduce":[97],"resolution":[99],"image":[102],"an":[104],"autoencoder":[105],"at":[107],"same":[109],"time":[110],"classify":[111],"it":[112],"another":[114],"network,":[115],"while":[116],"both":[117],"jointly.":[122],"algorithm":[124],"guides":[125],"model":[127],"learn":[129],"essential":[130],"representations":[131],"from":[132],"high-resolution":[133],"along":[137],"with":[138,165],"reconstruction.":[139],"We":[140],"have":[141,155,163],"publicly":[144],"available":[145],"dataset":[146,174],"chest":[148],"x-rays":[149],"evaluate":[151],"outperformed":[156],"state-of-the-art":[157],"on":[158],"test":[159],"data.":[160],"Besides,":[161],"experimented":[164],"effects":[167],"augmentation":[170],"approaches":[171],"report":[176],"baselines":[177],"some":[179],"well":[180],"known":[181],"class":[183],"CNNs.":[185]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
