{"id":"https://openalex.org/W7203827809","doi":"https://doi.org/10.1117/12.3119752","title":"PFT-Net: prototypes filtering and transformation for few-shot medical image segmentation","display_name":"PFT-Net: prototypes filtering and transformation for few-shot medical image segmentation","publication_year":2026,"publication_date":"2026-08-20","ids":{"openalex":"https://openalex.org/W7203827809","doi":"https://doi.org/10.1117/12.3119752"},"language":"en","primary_location":{"id":"doi:10.1117/12.3119752","doi":"https://doi.org/10.1117/12.3119752","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.3119752","pdf_url":null,"source":{"id":"https://openalex.org/S4306419342","display_name":"International Conference on Digital Image Processing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Eighteenth International Conference on Digital Image Processing (ICDIP 2026)","raw_type":"proceedings-article"},"volume":null,"type":"conference-abstract","is_traditional":false,"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/A5147636899","display_name":"Ruibin Zhou","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruibin Zhou","raw_affiliation_strings":["Guangdong University of Technology (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong University of Technology (China)","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006709942","display_name":"Guoheng Huang","orcid":"https://orcid.org/0000-0002-3640-3229","observed_orcids":["https://orcid.org/0000-0002-3640-3229"]},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoheng Huang","raw_affiliation_strings":["Guangdong University of Technology (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong University of Technology (China)","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5147658829","display_name":"Linhui Wu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linhui Wu","raw_affiliation_strings":["Guangdong University of Technology (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong University of Technology (China)","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5147470970","display_name":"Ming Li","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I135237710","display_name":"Zhejiang Normal University","ror":"https://ror.org/01vevwk45","country_code":"CN","type":"education","lineage":["https://openalex.org/I135237710"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Li","raw_affiliation_strings":["Zhejiang Normal University (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang Normal University (China)","institution_ids":["https://openalex.org/I135237710"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130244791","display_name":"Yan Li","orcid":"https://orcid.org/0009-0006-9503-1441","observed_orcids":["https://orcid.org/0009-0006-9503-1441"]},"institutions":[{"id":"https://openalex.org/I182722699","display_name":"Shenzhen Polytechnic University","ror":"https://ror.org/00d2w9g53","country_code":"CN","type":"education","lineage":["https://openalex.org/I182722699"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Li","raw_affiliation_strings":["Shenzhen Polytechnic University (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Polytechnic University (China)","institution_ids":["https://openalex.org/I182722699"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051381076","display_name":"Xiaochen Yuan","orcid":"https://orcid.org/0000-0002-7490-6695","observed_orcids":["https://orcid.org/0000-0002-7490-6695"]},"institutions":[{"id":"https://openalex.org/I49835588","display_name":"Macao Polytechnic University","ror":"https://ror.org/02sf5td35","country_code":"MO","type":"education","lineage":["https://openalex.org/I49835588"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Xiaochen Yuan","raw_affiliation_strings":["Macao Polytechnic University (Macao, China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Macao Polytechnic University (Macao, China)","institution_ids":["https://openalex.org/I49835588"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032362514","display_name":"Lianglun Cheng","orcid":"https://orcid.org/0000-0002-8213-041X","observed_orcids":["https://orcid.org/0000-0002-8213-041X"]},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianglun Cheng","raw_affiliation_strings":["Guangdong University of Technology (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong University of Technology (China)","institution_ids":["https://openalex.org/I139024713"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"65","last_page":"65"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9810000061988831,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9810000061988831,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.018699999898672104,"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":0.00019999999494757503,"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/intra-class-variation","display_name":"intra-class variation","score":0.871999979019165},{"id":"https://openalex.org/keywords/optimal-transport","display_name":"optimal transport","score":0.984000027179718},{"id":"https://openalex.org/keywords/organ-segmentation","display_name":"organ segmentation","score":0.5099999904632568}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7105000019073486},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6679999828338623},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6015999913215637},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.49630001187324524},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.475600004196167},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.46810001134872437},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.43639999628067017},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36079999804496765},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.352400004863739},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.3465000092983246},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.34290000796318054},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3264999985694885},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.26499998569488525},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.26350000500679016}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.3119752","doi":"https://doi.org/10.1117/12.3119752","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.3119752","pdf_url":null,"source":{"id":"https://openalex.org/S4306419342","display_name":"International Conference on Digital Image Processing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Eighteenth International Conference on Digital Image Processing (ICDIP 2026)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7165955395","https://openalex.org/W4414349404","https://openalex.org/W4396781531","https://openalex.org/W7134186791","https://openalex.org/W4412830029","https://openalex.org/W4416441574","https://openalex.org/W4408993081","https://openalex.org/W4387211355","https://openalex.org/W4406238174","https://openalex.org/W7154598316"],"abstract_inverted_index":{"In":[0,77],"few-shot":[1],"medical":[2,60,200],"image":[3,201],"segmentation":[4,31,72,202],"(FSMIS),":[5],"the":[6,30,33,39,58,91,108,124,130,140,150,156,170,174,179,183,187,221,224],"mainstream":[7],"methods":[8,218],"typically":[9],"adopt":[10],"prototype-driven":[11],"methods,":[12],"which":[13,148],"use":[14],"Masked":[15],"Average":[16],"Pooling":[17],"(MAP)":[18],"to":[19,28,38,57,70,89,117,154,166],"extract":[20],"class":[21,132],"centers":[22],"(prototypes)":[23],"from":[24],"labeled":[25],"support":[26,68,159,191],"samples":[27],"guide":[29],"of":[32,42,110,126,129,173,223],"query":[34,71,175,193],"image.":[35,176],"However,":[36],"due":[37],"inherent":[40],"diversity":[41],"organs,":[43],"significant":[44],"variations":[45],"in":[46,113],"feature":[47,171],"distributions":[48],"(intra-class":[49],"variation)":[50],"may":[51],"still":[52],"exist":[53],"among":[54],"organs":[55],"belonging":[56],"same":[59],"category.":[61],"Limited":[62],"by":[63],"this":[64,78],"phenomenon,":[65],"directly":[66],"applying":[67],"prototypes":[69,160],"often":[73],"yields":[74],"suboptimal":[75],"performance.":[76],"paper,":[79],"we":[80,138],"propose":[81],"a":[82,96,114],"Prototypes":[83,98,144],"Filtering":[84,99],"and":[85,133,192,207,219],"Transformation":[86,145],"Network":[87],"(PFT-Net)":[88],"alleviate":[90],"intra-class":[92,188],"variation":[93,189],"problem.":[94],"Firstly,":[95],"Self-Feedback":[97],"(SFPF)":[100],"module":[101],"is":[102,229],"designed.":[103],"Specifically,":[104],"SFPF":[105],"iteratively":[106],"filters":[107],"features":[109],"heterogeneous":[111,135],"regions":[112],"self-feedback":[115],"manner":[116],"form":[118],"more":[119],"robust":[120],"prototypes.":[121],"This":[122],"maximizes":[123],"extraction":[125],"high-quality":[127],"semantics":[128],"target":[131],"discards":[134],"semantics.":[136],"Second,":[137],"introduce":[139],"Optimal":[141],"Transport":[142],"based":[143],"(OTPT)":[146],"module,":[147],"employs":[149],"optimal":[151],"transport":[152],"algorithm":[153],"convert":[155],"initially":[157],"filtered":[158],"into":[161],"query-adapted":[162],"representations,":[163],"allowing":[164],"them":[165],"better":[167],"align":[168],"with":[169],"distribution":[172],"By":[177],"integrating":[178],"two":[180],"proposed":[181,225],"modules,":[182],"model":[184],"effectively":[185],"mitigates":[186],"between":[190],"samples.":[194],"Experimental":[195],"results":[196],"on":[197,205,209],"three":[198],"benchmark":[199],"datasets":[203],"(0.93%":[204],"CHAOS-T2":[206],"1.93%":[208],"Synapse)":[210],"demonstrate":[211],"that":[212],"PFT-Net":[213],"outperforms":[214],"state-ofthe-":[215],"art":[216],"FSMIS":[217],"verify":[220],"effectiveness":[222],"modules.":[226],"The":[227],"code":[228],"available":[230],"at:":[231],"https://github.com/zhouruibin/PFT-Net.":[232]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-08-21T00:00:00"}
