{"id":"https://openalex.org/W4415482613","doi":"https://doi.org/10.1109/access.2025.3624818","title":"Test-Time Confidence-Aware Query Labeling Improves 3D Few-Shot Segmentation","display_name":"Test-Time Confidence-Aware Query Labeling Improves 3D Few-Shot Segmentation","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4415482613","doi":"https://doi.org/10.1109/access.2025.3624818"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3624818","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3624818","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3624818","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Mohammad Mozafari","orcid":"https://orcid.org/0009-0001-6387-4827"},"institutions":[{"id":"https://openalex.org/I133529467","display_name":"Sharif University of Technology","ror":"https://ror.org/024c2fq17","country_code":"IR","type":"education","lineage":["https://openalex.org/I133529467"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mohammad Mozafari","raw_affiliation_strings":["Sharif University of Technology, Tehran, Iran"],"raw_orcid":"https://orcid.org/0009-0001-6387-4827","affiliations":[{"raw_affiliation_string":"Sharif University of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I133529467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102776829","display_name":"Hosein Hasani","orcid":"https://orcid.org/0009-0002-6234-897X"},"institutions":[{"id":"https://openalex.org/I133529467","display_name":"Sharif University of Technology","ror":"https://ror.org/024c2fq17","country_code":"IR","type":"education","lineage":["https://openalex.org/I133529467"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Hosein Hasani","raw_affiliation_strings":["Sharif University of Technology, Tehran, Iran"],"raw_orcid":"https://orcid.org/0009-0002-6234-897X","affiliations":[{"raw_affiliation_string":"Sharif University of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I133529467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114334979","display_name":"Reza Vahidimajd","orcid":"https://orcid.org/0009-0005-0072-1179"},"institutions":[{"id":"https://openalex.org/I133529467","display_name":"Sharif University of Technology","ror":"https://ror.org/024c2fq17","country_code":"IR","type":"education","lineage":["https://openalex.org/I133529467"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Reza Vahidimajd","raw_affiliation_strings":["Sharif University of Technology, Tehran, Iran"],"raw_orcid":"https://orcid.org/0009-0005-0072-1179","affiliations":[{"raw_affiliation_string":"Sharif University of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I133529467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004364890","display_name":"Mohamadreza Fereydooni","orcid":null},"institutions":[{"id":"https://openalex.org/I133529467","display_name":"Sharif University of Technology","ror":"https://ror.org/024c2fq17","country_code":"IR","type":"education","lineage":["https://openalex.org/I133529467"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mohamadreza Fereydooni","raw_affiliation_strings":["Sharif University of Technology, Tehran, Iran"],"raw_orcid":"https://orcid.org/0009-0005-0502-185X","affiliations":[{"raw_affiliation_string":"Sharif University of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I133529467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069082023","display_name":"Mahdieh Soleymani Baghshah","orcid":"https://orcid.org/0000-0002-1971-6231"},"institutions":[{"id":"https://openalex.org/I133529467","display_name":"Sharif University of Technology","ror":"https://ror.org/024c2fq17","country_code":"IR","type":"education","lineage":["https://openalex.org/I133529467"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mahdieh Soleymani Baghshah","raw_affiliation_strings":["Sharif University of Technology, Tehran, Iran"],"raw_orcid":"https://orcid.org/0000-0002-1971-6231","affiliations":[{"raw_affiliation_string":"Sharif University of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I133529467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I133529467"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.40307757,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":null,"first_page":"186042","last_page":"186053"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9990000128746033,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9990000128746033,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9939000010490417,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.993399977684021,"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/segmentation","display_name":"Segmentation","score":0.7286999821662903},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7002999782562256},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.5044999718666077},{"id":"https://openalex.org/keywords/query-optimization","display_name":"Query optimization","score":0.428600013256073},{"id":"https://openalex.org/keywords/query-expansion","display_name":"Query expansion","score":0.3824000060558319},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.36489999294281006},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.3598000109195709},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.3578999936580658}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8511000275611877},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7286999821662903},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7002999782562256},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.5044999718666077},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4772000014781952},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.428600013256073},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42320001125335693},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.3824000060558319},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.36489999294281006},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.3598000109195709},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.3578999936580658},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3571000099182129},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.3278999924659729},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.29490000009536743},{"id":"https://openalex.org/C192028432","wikidata":"https://www.wikidata.org/wiki/Q845739","display_name":"Query language","level":2,"score":0.2890999913215637},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2865000069141388},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.27250000834465027},{"id":"https://openalex.org/C24028149","wikidata":"https://www.wikidata.org/wiki/Q7094056","display_name":"Online aggregation","level":5,"score":0.2687999904155731},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.265500009059906},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.2612000107765198},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25929999351501465},{"id":"https://openalex.org/C118689300","wikidata":"https://www.wikidata.org/wiki/Q7978614","display_name":"Web query classification","level":4,"score":0.25600001215934753}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3624818","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3624818","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:7ba3c502bd104deea7336c4b412ba5ec","is_oa":true,"landing_page_url":"https://doaj.org/article/7ba3c502bd104deea7336c4b412ba5ec","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":"IEEE Access, Vol 13, Pp 186042-186053 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3624818","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3624818","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0,65,89],"recent":[1],"years,":[2],"few-shot":[3,31],"segmentation":[4,32,109,126,175],"(FSS)":[5],"models":[6],"have":[7,33],"emerged":[8],"as":[9,55],"a":[10,74,94,119,133,139,172],"promising":[11],"approach":[12],"in":[13],"medical":[14,66],"imaging":[15],"analysis,":[16],"offering":[17],"remarkable":[18],"adaptability":[19],"to":[20,30,43,61,83,97,122,143,152],"segment":[21],"novel":[22,95],"classes":[23],"with":[24],"limited":[25],"annotated":[26],"data.":[27],"Existing":[28],"approaches":[29],"often":[34],"overlooked":[35],"the":[36,39,46,53,68,85,100,104,115,129,145,153,163,169,178,185],"potential":[37],"of":[38,71,77,103,149,171],"query":[40,54,105,130,150,179],"itself,":[41],"failing":[42],"fully":[44],"utilize":[45],"valuable":[47,75],"information":[48,78,102],"it":[49],"contains.":[50],"However,":[51],"treating":[52],"unlabeled":[56],"data":[57],"provides":[58,73],"an":[59,124],"opportunity":[60],"enhance":[62],"prediction":[63,158,170],"accuracy.":[64],"imaging,":[67],"volumetric":[69],"structure":[70],"queries":[72],"source":[76],"that":[79,184],"can":[80,188],"be":[81],"used":[82],"improve":[84],"target":[86],"slice":[87],"segmentation.":[88],"this":[90],"work,":[91],"we":[92,113,137],"present":[93],"strategy":[96],"efficiently":[98],"leverage":[99],"intrinsic":[101],"sample":[106],"for":[107,128,177],"final":[108,157],"during":[110],"inference.":[111],"First,":[112],"use":[114],"support":[116,154,166],"slices":[117,131,151],"from":[118],"reference":[120],"volume":[121],"generate":[123],"initial":[125],"score":[127],"through":[132],"prototypical":[134],"approach.":[135],"Subsequently,":[136],"apply":[138],"confidence-aware":[140],"pseudo-labeling":[141],"procedure":[142],"transfer":[144],"most":[146],"informative":[147],"parts":[148],"set.":[155],"The":[156],"is":[159],"performed":[160],"based":[161],"on":[162],"new":[164],"expanded":[165],"set,":[167],"enabling":[168],"more":[173],"accurate":[174],"mask":[176],"volume.":[180],"Extensive":[181],"experiments":[182],"show":[183],"proposed":[186],"method":[187],"effectively":[189],"boost":[190],"performance":[191],"across":[192],"diverse":[193],"settings":[194],"and":[195],"datasets.":[196]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-23T00:00:00"}