{"id":"https://openalex.org/W4410297802","doi":"https://doi.org/10.1109/isbi60581.2025.10981068","title":"Human-in-the-Loop Semi-Supervised Uterine Cervix Ultrasound Image Segmentation","display_name":"Human-in-the-Loop Semi-Supervised Uterine Cervix Ultrasound Image Segmentation","publication_year":2025,"publication_date":"2025-04-14","ids":{"openalex":"https://openalex.org/W4410297802","doi":"https://doi.org/10.1109/isbi60581.2025.10981068"},"language":"en","primary_location":{"id":"doi:10.1109/isbi60581.2025.10981068","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi60581.2025.10981068","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI)","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/A5112044388","display_name":"Nhat-Thang Tran","orcid":null},"institutions":[{"id":"https://openalex.org/I123565023","display_name":"Vietnam National University Ho Chi Minh City","ror":"https://ror.org/00waaqh38","country_code":"VN","type":"education","lineage":["https://openalex.org/I123565023"]}],"countries":["VN"],"is_corresponding":true,"raw_author_name":"Nam-Khanh Tran","raw_affiliation_strings":["University of Science, VNU-HCM Vietnam National University,Ho Chi Minh City,Vietnam"],"affiliations":[{"raw_affiliation_string":"University of Science, VNU-HCM Vietnam National University,Ho Chi Minh City,Vietnam","institution_ids":["https://openalex.org/I123565023"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5117518928","display_name":"Dac-Phu Phan-Le","orcid":null},"institutions":[{"id":"https://openalex.org/I123565023","display_name":"Vietnam National University Ho Chi Minh City","ror":"https://ror.org/00waaqh38","country_code":"VN","type":"education","lineage":["https://openalex.org/I123565023"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Dac-Phu Phan-Le","raw_affiliation_strings":["University of Science, VNU-HCM Vietnam National University,Ho Chi Minh City,Vietnam"],"affiliations":[{"raw_affiliation_string":"University of Science, VNU-HCM Vietnam National University,Ho Chi Minh City,Vietnam","institution_ids":["https://openalex.org/I123565023"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053495766","display_name":"Minh\u2013Triet Tran","orcid":"https://orcid.org/0000-0003-3046-3041"},"institutions":[{"id":"https://openalex.org/I123565023","display_name":"Vietnam National University Ho Chi Minh City","ror":"https://ror.org/00waaqh38","country_code":"VN","type":"education","lineage":["https://openalex.org/I123565023"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Minh-Triet Tran","raw_affiliation_strings":["University of Science, VNU-HCM Vietnam National University,Ho Chi Minh City,Vietnam"],"affiliations":[{"raw_affiliation_string":"University of Science, VNU-HCM Vietnam National University,Ho Chi Minh City,Vietnam","institution_ids":["https://openalex.org/I123565023"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101111461","display_name":"Hai-Dang Nguyen","orcid":null},"institutions":[{"id":"https://openalex.org/I123565023","display_name":"Vietnam National University Ho Chi Minh City","ror":"https://ror.org/00waaqh38","country_code":"VN","type":"education","lineage":["https://openalex.org/I123565023"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Hai-Dang Nguyen","raw_affiliation_strings":["University of Science, VNU-HCM Vietnam National University,Ho Chi Minh City,Vietnam"],"affiliations":[{"raw_affiliation_string":"University of Science, VNU-HCM Vietnam National University,Ho Chi Minh City,Vietnam","institution_ids":["https://openalex.org/I123565023"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5112044388"],"corresponding_institution_ids":["https://openalex.org/I123565023"],"apc_list":null,"apc_paid":null,"fwci":0.6954,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.68843936,"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":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.89410001039505,"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"}},"topics":[{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.89410001039505,"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/segmentation","display_name":"Segmentation","score":0.5469090342521667},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5425877571105957},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5312647223472595},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5230059027671814},{"id":"https://openalex.org/keywords/loop","display_name":"Loop (graph theory)","score":0.5096981525421143},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5014979839324951},{"id":"https://openalex.org/keywords/ultrasound","display_name":"Ultrasound","score":0.48054319620132446},{"id":"https://openalex.org/keywords/uterine-cervix","display_name":"Uterine cervix","score":0.4581540822982788},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.36876213550567627},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.34563007950782776},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13088274002075195},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.1007935106754303},{"id":"https://openalex.org/keywords/carcinoma","display_name":"Carcinoma","score":0.06693482398986816}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5469090342521667},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5425877571105957},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5312647223472595},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5230059027671814},{"id":"https://openalex.org/C184670325","wikidata":"https://www.wikidata.org/wiki/Q512604","display_name":"Loop (graph theory)","level":2,"score":0.5096981525421143},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5014979839324951},{"id":"https://openalex.org/C143753070","wikidata":"https://www.wikidata.org/wiki/Q162564","display_name":"Ultrasound","level":2,"score":0.48054319620132446},{"id":"https://openalex.org/C2992879611","wikidata":"https://www.wikidata.org/wiki/Q666412","display_name":"Uterine cervix","level":3,"score":0.4581540822982788},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.36876213550567627},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.34563007950782776},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13088274002075195},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.1007935106754303},{"id":"https://openalex.org/C2777546739","wikidata":"https://www.wikidata.org/wiki/Q33525","display_name":"Carcinoma","level":2,"score":0.06693482398986816},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi60581.2025.10981068","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi60581.2025.10981068","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2","score":0.5600000023841858}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2464708700","https://openalex.org/W2517954747","https://openalex.org/W2912989244","https://openalex.org/W2963785012","https://openalex.org/W3014974815","https://openalex.org/W3192495122","https://openalex.org/W3204025806","https://openalex.org/W4220886433","https://openalex.org/W4282935002","https://openalex.org/W4285553345","https://openalex.org/W4390561780","https://openalex.org/W4403150304"],"related_works":["https://openalex.org/W24774503","https://openalex.org/W2014821076","https://openalex.org/W1990620319","https://openalex.org/W1965744717","https://openalex.org/W2351153092","https://openalex.org/W2111234595","https://openalex.org/W3216334292","https://openalex.org/W1883238101","https://openalex.org/W2481821631","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Medical":[0],"image":[1,143],"segmentation":[2,68,111],"is":[3,49,59,64],"today":[4],"crucial":[5],"for":[6,51,87],"disease":[7],"diagnosis":[8],"and":[9,42,61,80,97,128],"treatment":[10],"planning,":[11],"yet":[12],"obtaining":[13],"high-quality":[14],"annotated":[15],"data":[16,89],"remains":[17],"a":[18,26,73,123,129],"significant":[19],"challenge.":[20],"In":[21],"this":[22],"paper,":[23],"we":[24],"propose":[25],"semi-supervised":[27],"learning":[28],"framework":[29],"leveraging":[30],"U-Net":[31],"as":[32],"the":[33,46,78,115,135],"baseline":[34],"model.":[35],"The":[36],"dataset":[37,79],"consists":[38],"of":[39,126,132,137],"both":[40],"labeled":[41,47],"unlabeled":[43,88],"images,":[44],"where":[45],"subset":[48],"used":[50],"initial":[52],"supervised":[53],"training.":[54],"To":[55],"improve":[56,81],"generalization,":[57],"cross-validation":[58],"employed,":[60],"model":[62,82],"ensembling":[63],"utilized":[65],"to":[66,76,93,109],"enhance":[67],"performance.":[69],"Our":[70],"approach":[71],"incorporates":[72],"human-in-the-loop":[74],"scheme":[75],"refine":[77],"performance":[83],"iteratively.":[84],"Predicted":[85],"masks":[86,100],"are":[90,101],"manually":[91],"corrected":[92],"remove":[94],"prominent":[95],"errors,":[96],"these":[98],"refined":[99],"progressively":[102],"integrated":[103],"into":[104],"subsequent":[105],"training":[106],"iterations,":[107],"leading":[108],"improved":[110],"accuracy.":[112],"Evaluated":[113],"on":[114],"public":[116],"FUGC":[117],"2025":[118],"leaderboard,":[119],"our":[120],"method":[121],"achieves":[122],"Dice":[124],"similarity":[125],"90.08%":[127],"Hausdorff":[130],"distance":[131],"40.39,":[133],"demon-strating":[134],"effectiveness":[136],"iterative":[138],"pseudo-label":[139],"refinement":[140],"in":[141],"ultrasound":[142],"segmentation.":[144]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}