{"id":"https://openalex.org/W3212580908","doi":"https://doi.org/10.1145/3474124.3474150","title":"Fusion Framework for Morphological and Multispectral Textural Features for Identification of Endometrial Tuberculosis","display_name":"Fusion Framework for Morphological and Multispectral Textural Features for Identification of Endometrial Tuberculosis","publication_year":2021,"publication_date":"2021-08-05","ids":{"openalex":"https://openalex.org/W3212580908","doi":"https://doi.org/10.1145/3474124.3474150","mag":"3212580908"},"language":"en","primary_location":{"id":"doi:10.1145/3474124.3474150","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3474124.3474150","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 Thirteenth International Conference on Contemporary Computing (IC3-2021)","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/A5028976780","display_name":"Varsha Garg","orcid":"https://orcid.org/0000-0003-0161-690X"},"institutions":[{"id":"https://openalex.org/I154970844","display_name":"Jaypee Institute of Information Technology","ror":"https://ror.org/05sttyy11","country_code":"IN","type":"education","lineage":["https://openalex.org/I154970844"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Varsha Garg","raw_affiliation_strings":["Jaypee Institute of Information Technology, India"],"affiliations":[{"raw_affiliation_string":"Jaypee Institute of Information Technology, India","institution_ids":["https://openalex.org/I154970844"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021852253","display_name":"Anita Sahoo","orcid":"https://orcid.org/0000-0002-2773-3728"},"institutions":[{"id":"https://openalex.org/I154970844","display_name":"Jaypee Institute of Information Technology","ror":"https://ror.org/05sttyy11","country_code":"IN","type":"education","lineage":["https://openalex.org/I154970844"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Anita Sahoo","raw_affiliation_strings":["Jaypee Institute of Information Technology, India"],"affiliations":[{"raw_affiliation_string":"Jaypee Institute of Information Technology, India","institution_ids":["https://openalex.org/I154970844"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005310746","display_name":"Vikas Saxena","orcid":"https://orcid.org/0000-0002-1698-1435"},"institutions":[{"id":"https://openalex.org/I154970844","display_name":"Jaypee Institute of Information Technology","ror":"https://ror.org/05sttyy11","country_code":"IN","type":"education","lineage":["https://openalex.org/I154970844"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vikas Saxena","raw_affiliation_strings":["Jaypee Institute of Information Technology, India"],"affiliations":[{"raw_affiliation_string":"Jaypee Institute of Information Technology, India","institution_ids":["https://openalex.org/I154970844"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5028976780"],"corresponding_institution_ids":["https://openalex.org/I154970844"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.21511874,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"187","last_page":"195"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12994","display_name":"Infrared Thermography in Medicine","score":0.978600025177002,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9785000085830688,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7952595949172974},{"id":"https://openalex.org/keywords/contourlet","display_name":"Contourlet","score":0.7564620971679688},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6837189793586731},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6392199993133545},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5824787616729736},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5347190499305725},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.4825419783592224},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47973600029945374},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.4765872657299042},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.4603843688964844},{"id":"https://openalex.org/keywords/tuberculosis","display_name":"Tuberculosis","score":0.4401496350765228},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2999187707901001},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.21820896863937378},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.1959621012210846},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.15475937724113464},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.10019007325172424}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7952595949172974},{"id":"https://openalex.org/C20479862","wikidata":"https://www.wikidata.org/wiki/Q5165589","display_name":"Contourlet","level":4,"score":0.7564620971679688},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6837189793586731},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6392199993133545},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5824787616729736},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5347190499305725},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.4825419783592224},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47973600029945374},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.4765872657299042},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.4603843688964844},{"id":"https://openalex.org/C2781069245","wikidata":"https://www.wikidata.org/wiki/Q12204","display_name":"Tuberculosis","level":2,"score":0.4401496350765228},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2999187707901001},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.21820896863937378},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.1959621012210846},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.15475937724113464},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.10019007325172424},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3474124.3474150","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3474124.3474150","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 Thirteenth International Conference on Contemporary Computing (IC3-2021)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W972269498","https://openalex.org/W1484777458","https://openalex.org/W2026517469","https://openalex.org/W2035433263","https://openalex.org/W2044465660","https://openalex.org/W2072965986","https://openalex.org/W2106002835","https://openalex.org/W2117403911","https://openalex.org/W2422427636","https://openalex.org/W2564921842","https://openalex.org/W2566352549","https://openalex.org/W2623612641","https://openalex.org/W2743243858","https://openalex.org/W2762666833","https://openalex.org/W2773877479","https://openalex.org/W2803801449","https://openalex.org/W2921702913","https://openalex.org/W2972631344","https://openalex.org/W2982660192","https://openalex.org/W3000128522","https://openalex.org/W3001756951","https://openalex.org/W3004808023","https://openalex.org/W3016323062","https://openalex.org/W3048392635","https://openalex.org/W3091273318","https://openalex.org/W3110443126","https://openalex.org/W3119100565","https://openalex.org/W4236322642","https://openalex.org/W4244442097","https://openalex.org/W4252052304","https://openalex.org/W6629052890"],"related_works":["https://openalex.org/W2363243283","https://openalex.org/W2363722403","https://openalex.org/W2388473933","https://openalex.org/W2025202639","https://openalex.org/W2803763537","https://openalex.org/W2036935742","https://openalex.org/W2412887622","https://openalex.org/W2115192025","https://openalex.org/W1669864993","https://openalex.org/W74665983"],"abstract_inverted_index":{"Endometrial":[0],"Tuberculosis":[1,15],"(ETB)":[2],"is":[3,31,43,104,119,194],"primarily":[4],"diagnosed":[5],"in":[6,70,97],"infertile":[7],"females":[8],"as":[9],"a":[10,100,180],"fallout":[11],"of":[12,32,40,49,57,117,125,156,177,183,192,199],"Female":[13],"Genital":[14],"(FGTB).":[16],"An":[17],"effective":[18,53],"and":[19,54,82,113,165],"fast":[20],"computational":[21],"method":[22],"to":[23,35,44,138,167],"diagnose":[24],"ETB":[25],"from":[26,66,78],"Transvaginal":[27],"ultrasound":[28],"(TVUS)":[29],"images":[30,59,65,128,143],"great":[33],"importance":[34],"the":[36,87,91,95,107,130,157,186,197,200],"community.":[37],"The":[38,63,171],"objective":[39],"this":[41],"paper":[42],"obtain":[45,139],"an":[46,52,114,175],"optimal":[47,115],"subset":[48,116],"features":[50,84,110,118],"for":[51,60,93,121,160,185,196],"discriminative":[55],"analysis":[56],"TVUS":[58,64,127],"identifying":[61,94],"ETB.":[62],"different":[67],"medical":[68],"centers":[69],"India":[71],"have":[72],"been":[73],"collected":[74],"under":[75],"expert":[76],"supervision":[77],"female":[79],"patients.":[80],"Texture":[81],"Morphological":[83],"effectively":[85],"capture":[86],"observations":[88],"made":[89],"by":[90],"experts":[92],"problem":[96],"hand.":[98],"Therefore":[99],"fusion":[101,158],"framework":[102],"model":[103,159],"proposed":[105,172],"where":[106],"extracted":[108],"image":[109],"are":[111,144],"fused":[112],"obtained":[120],"identification.":[122],"Multiresolution":[123],"transformation":[124],"ill-defined":[126],"highlights":[129],"directional,":[131],"multi-":[132],"scale":[133],"spectral":[134],"textural":[135,141],"features.":[136],"Therefore,":[137],"discriminatory":[140],"features,":[142],"transformed":[145],"using":[146],"Non-Subsampled":[147],"Contourlet":[148],"Transformation":[149],"(NSCT)":[150],"before":[151],"feature":[152,190,203],"extraction.":[153],"Experimental":[154],"results":[155],"classification":[161,198],"show":[162],"significant":[163],"improvements":[164],"prove":[166],"be":[168],"more":[169],"efficient.":[170],"methodology":[173],"records":[174],"F-score":[176],"0.845":[178],"with":[179],"sensitivity":[181],"score":[182],"0.818":[184],"dataset":[187,201],"available.":[188],"A":[189],"reduction":[191],"64.5%":[193],"attained":[195],"after":[202],"selection.":[204]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}