{"id":"https://openalex.org/W4388240488","doi":"https://doi.org/10.1109/mmul.2023.3329006","title":"Uncertainty-Guided Different Levels of Pseudolabels for Semisupervised Medical Image Segmentation","display_name":"Uncertainty-Guided Different Levels of Pseudolabels for Semisupervised Medical Image Segmentation","publication_year":2023,"publication_date":"2023-11-02","ids":{"openalex":"https://openalex.org/W4388240488","doi":"https://doi.org/10.1109/mmul.2023.3329006"},"language":"en","primary_location":{"id":"doi:10.1109/mmul.2023.3329006","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmul.2023.3329006","pdf_url":null,"source":{"id":"https://openalex.org/S72873717","display_name":"IEEE Multimedia","issn_l":"1070-986X","issn":["1070-986X","1941-0166"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 MultiMedia","raw_type":"journal-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/A5061129679","display_name":"H. B. Li","orcid":"https://orcid.org/0009-0008-3161-9419"},"institutions":[{"id":"https://openalex.org/I206324368","display_name":"Shaoyang University","ror":"https://ror.org/03fx09x73","country_code":"CN","type":"education","lineage":["https://openalex.org/I206324368"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hengfan Li","raw_affiliation_strings":["Shaoyang University, Shaoyang, China"],"raw_orcid":"https://orcid.org/0009-0008-3161-9419","affiliations":[{"raw_affiliation_string":"Shaoyang University, Shaoyang, China","institution_ids":["https://openalex.org/I206324368"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103449210","display_name":"Xinwei Hong","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinwei Hong","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068439289","display_name":"Guohua Huang","orcid":"https://orcid.org/0000-0001-6954-3933"},"institutions":[{"id":"https://openalex.org/I206324368","display_name":"Shaoyang University","ror":"https://ror.org/03fx09x73","country_code":"CN","type":"education","lineage":["https://openalex.org/I206324368"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guohua Huang","raw_affiliation_strings":["Shaoyang University, Shaoyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shaoyang University, Shaoyang, China","institution_ids":["https://openalex.org/I206324368"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037993842","display_name":"Xuanbo Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I74872605","display_name":"China Southern Power Grid (China)","ror":"https://ror.org/03hkh9419","country_code":"CN","type":"company","lineage":["https://openalex.org/I74872605"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuanbo Xu","raw_affiliation_strings":["Shantou Power Supply Bureau of Guangdong Power Grid, Shantou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shantou Power Supply Bureau of Guangdong Power Grid, Shantou, China","institution_ids":["https://openalex.org/I74872605"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013283955","display_name":"Qingfeng Xia","orcid":"https://orcid.org/0000-0003-0829-6750"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qingfeng Xia","raw_affiliation_strings":["Wuxi University, Wuxi, China"],"raw_orcid":"https://orcid.org/0000-0003-0829-6750","affiliations":[{"raw_affiliation_string":"Wuxi University, Wuxi, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2127,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.50734215,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"31","issue":"1","first_page":"42","last_page":"53"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9993000030517578,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9988999962806702,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9973999857902527,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7519110441207886},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.7328747510910034},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6114648580551147},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5523291230201721},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5051551461219788},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4980008602142334},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.4433836340904236},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.4297313094139099},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36482328176498413}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7519110441207886},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.7328747510910034},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6114648580551147},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5523291230201721},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5051551461219788},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4980008602142334},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.4433836340904236},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.4297313094139099},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36482328176498413}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mmul.2023.3329006","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmul.2023.3329006","pdf_url":null,"source":{"id":"https://openalex.org/S72873717","display_name":"IEEE Multimedia","issn_l":"1070-986X","issn":["1070-986X","1941-0166"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 MultiMedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.7799999713897705,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2962914239","https://openalex.org/W2963891950","https://openalex.org/W2979907638","https://openalex.org/W3014974815","https://openalex.org/W3093394156","https://openalex.org/W3112701542","https://openalex.org/W3156669901","https://openalex.org/W3205549779","https://openalex.org/W4225898646","https://openalex.org/W4283800702","https://openalex.org/W4285040393","https://openalex.org/W4311777178","https://openalex.org/W4317639940","https://openalex.org/W4375928887","https://openalex.org/W4384206867","https://openalex.org/W4385767742","https://openalex.org/W4387211364","https://openalex.org/W4387211627","https://openalex.org/W4387211674","https://openalex.org/W4387415409","https://openalex.org/W6963891028"],"related_works":["https://openalex.org/W4379231730","https://openalex.org/W4389858081","https://openalex.org/W2501551404","https://openalex.org/W4298131179","https://openalex.org/W2113201962","https://openalex.org/W4385583601","https://openalex.org/W4395685956","https://openalex.org/W1522196789","https://openalex.org/W4367060753","https://openalex.org/W4379141755"],"abstract_inverted_index":{"The":[0,44,72,121],"significance":[1],"of":[2,32,47],"low-quality":[3],"data":[4,17,40],"in":[5,41,86,96],"unlabeled":[6],"medical":[7,42],"images":[8],"is":[9,125],"always":[10],"underestimated.":[11],"We":[12,25,108],"believe":[13],"that":[14,21,51],"these":[15],"underestimated":[16,39],"contain":[18],"valuable":[19],"information":[20,103],"remains":[22],"largely":[23],"unexplored.":[24],"present":[26],"a":[27,48,110],"novel":[28],"uncertainty-guided":[29],"different":[30],"levels":[31],"pseudo-labels":[33,57],"(UDLP)":[34],"framework":[35,45,123],"to":[36,54,99,116,135],"explore":[37],"the":[38,56,60,82,89,93,105],"images.":[43],"consists":[46],"student-teacher":[49],"model":[50,62,74,91],"uses":[52],"uncertainty":[53],"classify":[55],"predicted":[58],"by":[59],"teacher":[61,90],"into":[63],"three":[64],"levels:":[65],"high":[66],"confidence,":[67],"low":[68],"confidence":[69],"and":[70,130],"unreliability.":[71],"student":[73,106],"learns":[75],"directly":[76],"from":[77],"high-confidence":[78],"pseudo-labels.":[79],"By":[80],"using":[81],"confident":[83],"learning":[84],"method":[85,111],"low-confidence":[87,97],"pseudo-labels,":[88,115],"corrects":[92],"noisy":[94],"labels":[95],"voxels":[98],"provide":[100],"positive":[101],"feature":[102],"for":[104,112],"model.":[107],"design":[109],"removing":[113],"unreliable":[114],"further":[117],"enhance":[118],"model\u2019s":[119],"generalizability.":[120],"proposed":[122],"UDLP":[124],"evaluated":[126],"on":[127],"two":[128],"datasets":[129],"demonstrates":[131],"superior":[132],"performance":[133],"compared":[134],"other":[136],"state-of-the-art":[137],"methods.":[138]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}