{"id":"https://openalex.org/W4207062733","doi":"https://doi.org/10.2478/acss-2021-0023","title":"Determining and Measuring the Amount of Region Having COVID-19 on Lung Images","display_name":"Determining and Measuring the Amount of Region Having COVID-19 on Lung Images","publication_year":2021,"publication_date":"2021-12-01","ids":{"openalex":"https://openalex.org/W4207062733","doi":"https://doi.org/10.2478/acss-2021-0023"},"language":"en","primary_location":{"id":"doi:10.2478/acss-2021-0023","is_oa":true,"landing_page_url":"https://doi.org/10.2478/acss-2021-0023","pdf_url":"https://www.sciendo.com/pdf/10.2478/acss-2021-0023","source":{"id":"https://openalex.org/S2737199380","display_name":"Applied Computer Systems","issn_l":"2255-8683","issn":["2255-8683","2255-8691"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310317398","host_organization_name":"Polish Association for Knowledge Promotion","host_organization_lineage":["https://openalex.org/P4310317398"],"host_organization_lineage_names":["Polish Association for Knowledge Promotion"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Computer Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.sciendo.com/pdf/10.2478/acss-2021-0023","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004319915","display_name":"Seda Arslan Tuncer","orcid":"https://orcid.org/0000-0001-6472-8306"},"institutions":[{"id":"https://openalex.org/I143396566","display_name":"F\u0131rat University","ror":"https://ror.org/05teb7b63","country_code":"TR","type":"education","lineage":["https://openalex.org/I143396566"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Seda Arslan Tuncer","raw_affiliation_strings":["Firat University, Software Engineering , Elazig , Turkey"],"raw_orcid":"https://orcid.org/0000-0001-6472-8306","affiliations":[{"raw_affiliation_string":"Firat University, Software Engineering , Elazig , Turkey","institution_ids":["https://openalex.org/I143396566"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061046364","display_name":"Ahmet \u00c7\u0131nar","orcid":"https://orcid.org/0000-0001-5528-2226"},"institutions":[{"id":"https://openalex.org/I143396566","display_name":"F\u0131rat University","ror":"https://ror.org/05teb7b63","country_code":"TR","type":"education","lineage":["https://openalex.org/I143396566"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Ahmet \u00c7\u0131nar","raw_affiliation_strings":["Firat University, Computer Engineering , Elazig , Turkey"],"raw_orcid":"https://orcid.org/0000-0001-5528-2226","affiliations":[{"raw_affiliation_string":"Firat University, Computer Engineering , Elazig , Turkey","institution_ids":["https://openalex.org/I143396566"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007371615","display_name":"Taner Tuncer","orcid":"https://orcid.org/0000-0003-0526-4526"},"institutions":[{"id":"https://openalex.org/I143396566","display_name":"F\u0131rat University","ror":"https://ror.org/05teb7b63","country_code":"TR","type":"education","lineage":["https://openalex.org/I143396566"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Taner Tuncer","raw_affiliation_strings":["Firat University, Computer Engineering , Elazig , Turkey"],"raw_orcid":"https://orcid.org/0000-0003-0526-4526","affiliations":[{"raw_affiliation_string":"Firat University, Computer Engineering , Elazig , Turkey","institution_ids":["https://openalex.org/I143396566"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076029715","display_name":"Fatih \u00c7olak","orcid":"https://orcid.org/0000-0001-7083-6135"},"institutions":[{"id":"https://openalex.org/I4210144819","display_name":"Elaz\u0131\u011f E\u011fitim ve Ara\u015ft\u0131rma Hastanesi","ror":"https://ror.org/03dwvx056","country_code":"TR","type":"healthcare","lineage":["https://openalex.org/I4210144819"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Fatih \u00c7olak","raw_affiliation_strings":["Kovanc\u0131lar Healthy Clinic , Elazig , Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kovanc\u0131lar Healthy Clinic , Elazig , Turkey","institution_ids":["https://openalex.org/I4210144819"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5007371615"],"corresponding_institution_ids":["https://openalex.org/I143396566"],"apc_list":null,"apc_paid":null,"fwci":0.1434,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.53841675,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"26","issue":"2","first_page":"183","last_page":"193"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":1.0,"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":1.0,"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":0.9983000159263611,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9854999780654907,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/jaccard-index","display_name":"Jaccard index","score":0.9389086961746216},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7312325239181519},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.6068147420883179},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6010869145393372},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5922099947929382},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.592082142829895},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5695295333862305},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5146163702011108},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.49610504508018494},{"id":"https://openalex.org/keywords/s\u00f8rensen\u2013dice-coefficient","display_name":"S\u00f8rensen\u2013Dice coefficient","score":0.47201722860336304},{"id":"https://openalex.org/keywords/lung","display_name":"Lung","score":0.45955145359039307},{"id":"https://openalex.org/keywords/dice","display_name":"Dice","score":0.45122355222702026},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.4311816096305847},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.426935613155365},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4125266969203949},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.39926642179489136},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2852562665939331},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.28501325845718384},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2257544994354248},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.16356372833251953},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.13607800006866455},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.10342240333557129}],"concepts":[{"id":"https://openalex.org/C203519979","wikidata":"https://www.wikidata.org/wiki/Q865360","display_name":"Jaccard index","level":3,"score":0.9389086961746216},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7312325239181519},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.6068147420883179},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6010869145393372},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5922099947929382},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.592082142829895},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5695295333862305},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5146163702011108},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.49610504508018494},{"id":"https://openalex.org/C163892561","wikidata":"https://www.wikidata.org/wiki/Q2613728","display_name":"S\u00f8rensen\u2013Dice coefficient","level":4,"score":0.47201722860336304},{"id":"https://openalex.org/C2777714996","wikidata":"https://www.wikidata.org/wiki/Q7886","display_name":"Lung","level":2,"score":0.45955145359039307},{"id":"https://openalex.org/C22029948","wikidata":"https://www.wikidata.org/wiki/Q45089","display_name":"Dice","level":2,"score":0.45122355222702026},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.4311816096305847},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.426935613155365},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4125266969203949},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.39926642179489136},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2852562665939331},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.28501325845718384},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2257544994354248},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.16356372833251953},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.13607800006866455},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.10342240333557129},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.2478/acss-2021-0023","is_oa":true,"landing_page_url":"https://doi.org/10.2478/acss-2021-0023","pdf_url":"https://www.sciendo.com/pdf/10.2478/acss-2021-0023","source":{"id":"https://openalex.org/S2737199380","display_name":"Applied Computer Systems","issn_l":"2255-8683","issn":["2255-8683","2255-8691"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310317398","host_organization_name":"Polish Association for Knowledge Promotion","host_organization_lineage":["https://openalex.org/P4310317398"],"host_organization_lineage_names":["Polish Association for Knowledge Promotion"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Computer Systems","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:a3328f25d7c14350ba3b819f6d7030b7","is_oa":true,"landing_page_url":"https://doaj.org/article/a3328f25d7c14350ba3b819f6d7030b7","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Applied Computer Systems, Vol 26, Iss 2, Pp 183-193 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.2478/acss-2021-0023","is_oa":true,"landing_page_url":"https://doi.org/10.2478/acss-2021-0023","pdf_url":"https://www.sciendo.com/pdf/10.2478/acss-2021-0023","source":{"id":"https://openalex.org/S2737199380","display_name":"Applied Computer Systems","issn_l":"2255-8683","issn":["2255-8683","2255-8691"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310317398","host_organization_name":"Polish Association for Knowledge Promotion","host_organization_lineage":["https://openalex.org/P4310317398"],"host_organization_lineage_names":["Polish Association for Knowledge Promotion"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Computer Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.8299999833106995}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4207062733.pdf","grobid_xml":"https://content.openalex.org/works/W4207062733.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2034656920","https://openalex.org/W2133665775","https://openalex.org/W2293099464","https://openalex.org/W2888436377","https://openalex.org/W2913637767","https://openalex.org/W2944800263","https://openalex.org/W2979751829","https://openalex.org/W2996131899","https://openalex.org/W3008167392","https://openalex.org/W3011414569","https://openalex.org/W3012916860","https://openalex.org/W3014924062","https://openalex.org/W3015284453","https://openalex.org/W3015609527","https://openalex.org/W3016595824","https://openalex.org/W3016912206","https://openalex.org/W3017855299","https://openalex.org/W3018936110","https://openalex.org/W3019268988","https://openalex.org/W3023908178","https://openalex.org/W3025576489","https://openalex.org/W3027763298","https://openalex.org/W3030621456","https://openalex.org/W3035268411","https://openalex.org/W3037414627","https://openalex.org/W3039137888","https://openalex.org/W3043933124","https://openalex.org/W3044055485","https://openalex.org/W3044548337","https://openalex.org/W3047502985","https://openalex.org/W3083891697","https://openalex.org/W3096956107","https://openalex.org/W3156862851","https://openalex.org/W3208176997"],"related_works":["https://openalex.org/W2553941787","https://openalex.org/W3012828488","https://openalex.org/W2953570019","https://openalex.org/W4389060404","https://openalex.org/W2973136608","https://openalex.org/W4286233748","https://openalex.org/W3116883888","https://openalex.org/W4367019122","https://openalex.org/W2046969815","https://openalex.org/W4287631720"],"abstract_inverted_index":{"Abstract":[0],"It":[1],"is":[2,191,195],"important":[3],"to":[4,102,124,184],"know":[5],"how":[6,62],"much":[7],"the":[8,13,16,33,39,42,48,63,68,107,118,125,178,185,198,201,216,224],"lungs":[9],"are":[10,115,121,152,167],"affected":[11],"in":[12,18,200],"course":[14],"of":[15,41,127,180,226],"disease":[17,34],"patients":[19],"with":[20,65,109,197],"COVID-19.":[21],"Detecting":[22],"infected":[23],"tissues":[24,108],"on":[25,70,111,188],"CT":[26,72,91,99,189],"lung":[27,69,113,186],"images":[28,190],"not":[29],"only":[30],"helps":[31,37],"diagnose":[32],"but":[35],"also":[36],"measure":[38],"severity":[40],"disease.":[43],"In":[44],"this":[45,86],"paper,":[46],"using":[47],"hybrid":[49,75],"artificial":[50,212],"intelligence-based":[51,213],"segmentation":[52,79],"method,":[53],"which":[54],"we":[55],"call":[56],"TA-Segnet,":[57],"it":[58],"has":[59,82],"been":[60,83],"revealed":[61],"region":[64,187],"COVID-19":[66,110,181,227],"affects":[67],"2D":[71],"images.":[73],"A":[74],"convolutional":[76],"neural":[77],"network-based":[78],"method":[80,214],"(TA-Segnet)":[81],"developed":[84],"for":[85,149],"process.":[87],"We":[88],"use":[89],"\u201cCOVID-19":[90,98],"Lung":[92],"and":[93,97,136,146,159,174,222],"Infection":[94],"Segmentation":[95,100],"Dataset\u201d":[96,101],"evaluate":[103],"TA-SegNET.":[104],"At":[105],"first,":[106],"each":[112],"image":[114],"determined,":[116],"then":[117],"measurements":[119],"obtained":[120,207],"evaluated":[122],"according":[123],"parameters":[126,166],"Accuracy,":[128,138],"Dice,":[129,139],"Jaccard,":[130,140],"Mean":[131,141],"Square":[132,142],"Error,":[133,143],"Mutual":[134,144],"Information":[135,145],"Cross-correlation.":[137],"Cross-correlation":[147],"values":[148,199],"data":[150,163,203],"set-1":[151],"98.63":[153],"%,":[154,169],"0.95,":[155],"0.919,":[156],"0.139,":[157],"0.51,":[158],"0.904,":[160],"respectively.":[161,176],"For":[162],"set-2,":[164],"these":[165],"98.57":[168],"0.958,":[170],"0.992,":[171],"0.0088,":[172],"0.565":[173],"0.8995,":[175],"Second,":[177],"ratio":[179,194],"regions":[182],"relative":[183],"determined.":[192],"This":[193],"compared":[196],"original":[202],"set.":[204],"The":[205],"results":[206],"show":[208],"that":[209],"such":[210],"an":[211],"during":[215],"pandemic":[217],"period":[218],"will":[219],"help":[220],"prioritize":[221],"automate":[223],"diagnosis":[225],"patients.":[228]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2022-01-26T00:00:00"}