{"id":"https://openalex.org/W4225736940","doi":"https://doi.org/10.1109/robio54168.2021.9739504","title":"Unseen Domain Generalization for Prostate MRI Segmentation via Disentangled Representations","display_name":"Unseen Domain Generalization for Prostate MRI Segmentation via Disentangled Representations","publication_year":2021,"publication_date":"2021-12-27","ids":{"openalex":"https://openalex.org/W4225736940","doi":"https://doi.org/10.1109/robio54168.2021.9739504"},"language":"en","primary_location":{"id":"doi:10.1109/robio54168.2021.9739504","is_oa":false,"landing_page_url":"https://doi.org/10.1109/robio54168.2021.9739504","pdf_url":null,"source":{"id":"https://openalex.org/S4363607846","display_name":"2021 IEEE International Conference on Robotics and Biomimetics (ROBIO)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Robotics and Biomimetics (ROBIO)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5023557586","display_name":"Ye Lu","orcid":"https://orcid.org/0000-0003-0805-6394"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Ye Lu","raw_affiliation_strings":["The Chinese University of Hong Kong,The Department of Electronic Engineering,Hong Kong,SAR,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong,The Department of Electronic Engineering,Hong Kong,SAR,China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080589649","display_name":"Xiaohan Xing","orcid":"https://orcid.org/0000-0002-9992-3387"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xiaohan Xing","raw_affiliation_strings":["The Chinese University of Hong Kong,The Department of Electronic Engineering,Hong Kong,SAR,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong,The Department of Electronic Engineering,Hong Kong,SAR,China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021531143","display_name":"Max Q.\u2010H. Meng","orcid":"https://orcid.org/0000-0002-5255-5898"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]},{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]},{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["CN","HK"],"is_corresponding":false,"raw_author_name":"Max Q.-H. Meng","raw_affiliation_strings":["The Southern University of Science and Technology,The Department of Electronic and Electrical Engineering,Shenzhen,China","The Shenzhen Research Institute of the Chinese, University of Hong Kong, Shenzhen, China","The Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong","The Department of Electronic and Electrical Engineering, The Southern University of Science and Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Southern University of Science and Technology,The Department of Electronic and Electrical Engineering,Shenzhen,China","institution_ids":["https://openalex.org/I3045169105"]},{"raw_affiliation_string":"The Shenzhen Research Institute of the Chinese, University of Hong Kong, Shenzhen, China","institution_ids":["https://openalex.org/I4210116924","https://openalex.org/I889458895"]},{"raw_affiliation_string":"The Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]},{"raw_affiliation_string":"The Department of Electronic and Electrical Engineering, The Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]}],"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":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1986","last_page":"1991"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9991000294685364,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9991000294685364,"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":0.9951000213623047,"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":0.9944000244140625,"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":0.7899799346923828},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7581932544708252},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7163066267967224},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.7156080007553101},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6272742748260498},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5970507264137268},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5487089157104492},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5087712407112122},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49262696504592896},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48711371421813965},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4148483872413635},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38788142800331116},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35439008474349976},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1421431303024292}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7899799346923828},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7581932544708252},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7163066267967224},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.7156080007553101},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6272742748260498},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5970507264137268},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5487089157104492},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5087712407112122},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49262696504592896},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48711371421813965},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4148483872413635},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38788142800331116},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35439008474349976},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1421431303024292},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/robio54168.2021.9739504","is_oa":false,"landing_page_url":"https://doi.org/10.1109/robio54168.2021.9739504","pdf_url":null,"source":{"id":"https://openalex.org/S4363607846","display_name":"2021 IEEE International Conference on Robotics and Biomimetics (ROBIO)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Robotics and Biomimetics (ROBIO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7400000095367432}],"awards":[],"funders":[{"id":"https://openalex.org/F4320335055","display_name":"Health and Medical Research Fund","ror":"https://ror.org/03qh32912"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1882958252","https://openalex.org/W2572730214","https://openalex.org/W2603777577","https://openalex.org/W2604790786","https://openalex.org/W2803620993","https://openalex.org/W2890435066","https://openalex.org/W2898192966","https://openalex.org/W2954234616","https://openalex.org/W2963890275","https://openalex.org/W3004531689","https://openalex.org/W3006040295","https://openalex.org/W3006326483","https://openalex.org/W3013916134","https://openalex.org/W3027069075","https://openalex.org/W3028433770","https://openalex.org/W3087667873","https://openalex.org/W3088349269","https://openalex.org/W3095569631","https://openalex.org/W3097096051","https://openalex.org/W3099805905","https://openalex.org/W3137695714","https://openalex.org/W3159890710","https://openalex.org/W6639480849","https://openalex.org/W6763485134","https://openalex.org/W6774896617"],"related_works":["https://openalex.org/W2118717649","https://openalex.org/W2413243053","https://openalex.org/W410723623","https://openalex.org/W2015341305","https://openalex.org/W2035068594","https://openalex.org/W4225593417","https://openalex.org/W2573498121","https://openalex.org/W3022298670","https://openalex.org/W3160494304","https://openalex.org/W2167883292"],"abstract_inverted_index":{"In":[0,46],"clinical":[1],"practice,":[2],"medical":[3],"images":[4],"obtained":[5],"from":[6,54],"different":[7],"sites":[8],"often":[9],"exhibit":[10],"appearance":[11,99],"variations,":[12],"resulting":[13],"in":[14,23,81],"limited":[15],"generalizability":[16],"of":[17,98,136],"deep":[18],"learning":[19],"models":[20],"for":[21,57,123],"segmentation":[22,60,76,92],"deployment.":[24],"It":[25],"is":[26,70],"an":[27],"important":[28],"but":[29],"challenging":[30],"task":[31],"to":[32,40,51,61,94,107],"train":[33],"a":[34,82,120],"model":[35,64,118],"which":[36],"can":[37],"directly":[38],"generalize":[39],"unseen":[41],"domains":[42],"with":[43,90],"distribution":[44],"shifts.":[45],"this":[47],"paper,":[48],"we":[49,102],"propose":[50],"disentangle":[52],"content":[53,68,88],"style":[55],"representations":[56],"prostate":[58,124],"MRI":[59,125],"improve":[62],"the":[63,75,87,91,96,110,134,140],"generalization,":[65],"considering":[66],"anatomical":[67],"information":[69],"domain":[71,105],"invariant":[72],"and":[73,129,143],"decides":[74],"masks.":[77],"Our":[78],"method":[79,142],"roots":[80],"representation":[83,112],"disentanglement":[84],"network,":[85],"sharing":[86],"encoder":[89],"module":[93],"remove":[95],"effect":[97],"discrepancy.":[100],"Besides,":[101],"introduce":[103],"two":[104],"discriminators":[106],"further":[108],"regularize":[109],"disentangled":[111],"learning.":[113],"We":[114],"extensively":[115],"validate":[116],"our":[117,137],"on":[119],"multi-site":[121],"dataset":[122],"segmentation.":[126],"Both":[127],"quantitative":[128],"qualitative":[130],"experimental":[131],"results":[132],"demonstrate":[133],"effectiveness":[135],"method,":[138],"outperforming":[139],"baseline":[141],"many":[144],"state-of-the-art":[145],"generalization":[146],"methods.":[147]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
