{"id":"https://openalex.org/W4210480923","doi":"https://doi.org/10.1109/tmi.2022.3149171","title":"Chest X-Ray Diagnostic Quality Assessment: How Much Is Pixel-Wise Supervision Needed?","display_name":"Chest X-Ray Diagnostic Quality Assessment: How Much Is Pixel-Wise Supervision Needed?","publication_year":2022,"publication_date":"2022-02-04","ids":{"openalex":"https://openalex.org/W4210480923","doi":"https://doi.org/10.1109/tmi.2022.3149171","pmid":"https://pubmed.ncbi.nlm.nih.gov/35120002"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2022.3149171","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2022.3149171","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Junhao Hu","orcid":"https://orcid.org/0000-0002-2448-7453"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junhao Hu","raw_affiliation_strings":["School of Information Science and Technology, ShanghaiTech University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chenyang Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenyang Zhang","raw_affiliation_strings":["School of Information Science and Technology, ShanghaiTech University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Kang Zhou","orcid":"https://orcid.org/0000-0001-8789-4243"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kang Zhou","raw_affiliation_strings":["School of Information Science and Technology, ShanghaiTech University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"last","author":{"id":null,"display_name":"Shenghua Gao","orcid":"https://orcid.org/0000-0003-1626-2040"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shenghua Gao","raw_affiliation_strings":["School of Information Science and Technology, the Shanghai Engineering Research Center of Intelligent Vision and Imaging, and the Shanghai Engineering Research Center of Energy Efficient and Custom AI IC, ShanghaiTech University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, the Shanghai Engineering Research Center of Intelligent Vision and Imaging, and the Shanghai Engineering Research Center of Energy Efficient and Custom AI IC, ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I30809798"],"apc_list":null,"apc_paid":null,"fwci":1.729,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.82881669,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"41","issue":"7","first_page":"1711","last_page":"1723"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9376999735832214,"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":0.9376999735832214,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.014299999922513962,"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"}},{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.006200000178068876,"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/chest-radiograph","display_name":"Chest radiograph","score":0.8500000238418579},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6507999897003174},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.642799973487854},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.49129998683929443},{"id":"https://openalex.org/keywords/radiography","display_name":"Radiography","score":0.43790000677108765},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.4332999885082245},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.42669999599456787},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4172999858856201}],"concepts":[{"id":"https://openalex.org/C2781137159","wikidata":"https://www.wikidata.org/wiki/Q1283318","display_name":"Chest radiograph","level":3,"score":0.8500000238418579},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6507999897003174},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.642799973487854},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5782999992370605},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5623000264167786},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.49129998683929443},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.4796999990940094},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.4726000130176544},{"id":"https://openalex.org/C36454342","wikidata":"https://www.wikidata.org/wiki/Q245341","display_name":"Radiography","level":2,"score":0.43790000677108765},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.4332999885082245},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.42669999599456787},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4172999858856201},{"id":"https://openalex.org/C2778704086","wikidata":"https://www.wikidata.org/wiki/Q693058","display_name":"Chest pain","level":2,"score":0.3709000051021576},{"id":"https://openalex.org/C106436119","wikidata":"https://www.wikidata.org/wiki/Q836575","display_name":"Quality assurance","level":3,"score":0.3483999967575073},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34619998931884766},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.31630000472068787},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.31360000371932983},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3043000102043152},{"id":"https://openalex.org/C3020132585","wikidata":"https://www.wikidata.org/wiki/Q2671652","display_name":"Diagnostic accuracy","level":2,"score":0.3010999858379364},{"id":"https://openalex.org/C2780193326","wikidata":"https://www.wikidata.org/wiki/Q16343","display_name":"Clavicle","level":2,"score":0.2953999936580658},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.29089999198913574},{"id":"https://openalex.org/C19527891","wikidata":"https://www.wikidata.org/wiki/Q1120908","display_name":"Medical physics","level":1,"score":0.2856999933719635},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2831000089645386},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.2809999883174896},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.27810001373291016},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.27489998936653137},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25429999828338623}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008168","descriptor_name":"Lung","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D008168","descriptor_name":"Lung","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D008168","descriptor_name":"Lung","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D011859","descriptor_name":"Radiography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011859","descriptor_name":"Radiography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011859","descriptor_name":"Radiography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014965","descriptor_name":"X-Rays","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014965","descriptor_name":"X-Rays","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014965","descriptor_name":"X-Rays","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1109/tmi.2022.3149171","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2022.3149171","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},{"id":"pmid:35120002","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35120002","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on medical imaging","raw_type":null},{"id":"pmh:oai:hub.hku.hk:10722/345166","is_oa":false,"landing_page_url":"https://hub.hku.hk/handle/10722/345166","pdf_url":null,"source":{"id":"https://openalex.org/S4377196271","display_name":"The HKU Scholars Hub (University of Hong Kong)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I889458895","host_organization_name":"University of Hong Kong","host_organization_lineage":["https://openalex.org/I889458895"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1495267108","https://openalex.org/W1901129140","https://openalex.org/W2024798729","https://openalex.org/W2030928387","https://openalex.org/W2059862641","https://openalex.org/W2065742895","https://openalex.org/W2097117768","https://openalex.org/W2117539524","https://openalex.org/W2124351162","https://openalex.org/W2142514727","https://openalex.org/W2168804568","https://openalex.org/W2194775991","https://openalex.org/W2295107390","https://openalex.org/W2412782625","https://openalex.org/W2520861906","https://openalex.org/W2552414813","https://openalex.org/W2611650229","https://openalex.org/W2700195045","https://openalex.org/W2754887662","https://openalex.org/W2794103425","https://openalex.org/W2884585870","https://openalex.org/W2885112059","https://openalex.org/W2885373832","https://openalex.org/W2886327376","https://openalex.org/W2889246432","https://openalex.org/W2953809838","https://openalex.org/W2956648669","https://openalex.org/W2962708065","https://openalex.org/W2963150697","https://openalex.org/W2963446712","https://openalex.org/W2963466845","https://openalex.org/W2963660453","https://openalex.org/W2979455736","https://openalex.org/W2979929139","https://openalex.org/W2980311233","https://openalex.org/W2981689412","https://openalex.org/W3018407595","https://openalex.org/W3027779789","https://openalex.org/W3082755608","https://openalex.org/W3106546328","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6638667902","https://openalex.org/W6639867372","https://openalex.org/W6682889407","https://openalex.org/W6684191040","https://openalex.org/W6696085341","https://openalex.org/W6745119210","https://openalex.org/W6746693533","https://openalex.org/W6747758984","https://openalex.org/W6748557511","https://openalex.org/W6753441378","https://openalex.org/W6761685959","https://openalex.org/W6767465851","https://openalex.org/W6786402227"],"related_works":[],"abstract_inverted_index":{"Chest":[0,13],"X-ray":[1,69,216],"is":[2,18,161,254],"an":[3],"important":[4,246],"imaging":[5],"method":[6],"for":[7,20,60,108,116,203,214,252],"the":[8,21,24,38,44,47,75,109,112,143,149,154,180,194,208,229],"diagnosis":[9,22,34],"of":[10,23,46,78,156,196,210,231,263,288],"chest":[11,61,68,81,215,271,279,294],"diseases.":[12],"radiograph":[14,62,82,272],"diagnostic":[15,63,70,83,217],"quality":[16,64,71,84,117,150,218,289],"assessment":[17,118],"vital":[19],"disease":[25],"because":[26,111],"unqualified":[27],"radiographs":[28,280,295],"have":[29,57],"negative":[30],"impacts":[31],"on":[32,40,153,239,307],"doctors'":[33],"and":[35,53,94,128,146,189,201,242,256,285,305],"thus":[36],"increase":[37],"burden":[39],"patients":[41],"due":[42],"to":[43,134,141,173,185,192,236,261,301],"re-acquirement":[45],"radiographs.":[48],"So":[49],"far":[50],"no":[51],"algorithms":[52,223,304],"public":[54],"data":[55,273,309,313],"sets":[56],"been":[58],"developed":[59],"assessment.":[65,219],"Towards":[66],"effective":[67],"assessment,":[72],"we":[73,132,171,267],"analyze":[74],"image":[76,102],"characteristics":[77],"four":[79,286],"main":[80],"issues,":[85],"i.e.":[86],"Scapula":[87],"Overlapping":[88],"Lung,":[89],"Artifact,":[90],"Lung":[91],"Field":[92],"Loss,":[93],"Clavicle":[95],"Unflatness.":[96],"Our":[97],"experiments":[98,206],"show":[99],"that":[100,178,262],"general":[101,221],"classification":[103,160],"methods":[104],"are":[105,299],"not":[106],"competent":[107],"task":[110],"detailed":[113],"information":[114],"used":[115],"by":[119,125,165],"radiologists":[120],"cannot":[121],"be":[122,316],"fully":[123],"exploited":[124],"deep":[126,232],"CNNs":[127],"image-level":[129],"annotations.":[130],"Then":[131],"propose":[133,172],"leverage":[135],"a":[136,175,183,270],"multi-label":[137],"semantic":[138,197,282],"segmentation":[139,168,198,253,283],"framework":[140],"find":[142],"problematic":[144],"regions,":[145],"then":[147],"classify":[148],"issues":[151],"based":[152],"results":[155],"segmentation.":[157],"However,":[158,220],"subsequent":[159],"often":[162],"negatively":[163],"affected":[164],"certain":[166],"small":[167],"errors.":[169],"Therefore,":[170],"estimate":[174],"distance":[176,181],"map":[177],"measures":[179],"from":[182],"pixel":[184],"its":[186,258],"nearest":[187],"segment,":[188],"use":[190],"it":[191],"force":[193],"prediction":[195],"more":[199],"holistic":[200],"suitable":[202],"classification.":[204],"Extensive":[205],"validate":[207,244,302],"effectiveness":[209],"our":[211,303],"semantic-segmentation-based":[212],"solution":[213],"segmentation-based":[222],"requires":[224],"fine":[225,240],"pixel-wise":[226,247],"annotations":[227,241,248,284,298],"in":[228],"era":[230],"learning.":[233],"In":[234],"order":[235],"reduce":[237],"reliance":[238],"further":[243],"how":[245],"are,":[249],"weak":[250],"supervision":[251],"applied,":[255],"demonstrates":[257],"ability":[259],"close":[260],"full":[264],"supervision.":[265],"Finally,":[266],"present":[268],"ChestX-rayQuality,":[269],"set,":[274],"which":[275],"comprises":[276],"480":[277],"frontal-view":[278],"with":[281,296],"labels":[287],"issue.":[290],"Also,":[291],"other":[292],"1212":[293],"limited":[297],"imported":[300],"arguments":[306],"larger":[308],"set.":[310],"These":[311],"two":[312],"set":[314],"will":[315],"made":[317],"publicly":[318],"available.":[319]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5}],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2022-02-08T00:00:00"}
