{"id":"https://openalex.org/W4408935218","doi":"https://doi.org/10.1109/jbhi.2025.3549029","title":"Non-IID Medical Image Segmentation Based on Cascaded Diffusion Model for Diverse Multi-Center Scenarios","display_name":"Non-IID Medical Image Segmentation Based on Cascaded Diffusion Model for Diverse Multi-Center Scenarios","publication_year":2025,"publication_date":"2025-03-28","ids":{"openalex":"https://openalex.org/W4408935218","doi":"https://doi.org/10.1109/jbhi.2025.3549029","pmid":"https://pubmed.ncbi.nlm.nih.gov/40146649"},"language":"en","primary_location":{"id":"doi:10.1109/jbhi.2025.3549029","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2025.3549029","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Biomedical and Health Informatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5100332181","display_name":"Hanwen Zhang","orcid":"https://orcid.org/0000-0003-0180-0993"},"institutions":[{"id":"https://openalex.org/I4210128628","display_name":"Peking University Shenzhen Hospital","ror":"https://ror.org/03kkjyb15","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128628"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hanwen Zhang","raw_affiliation_strings":["Peking University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Shenzhen, China","institution_ids":["https://openalex.org/I4210128628"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101538376","display_name":"Mingzhi Chen","orcid":"https://orcid.org/0000-0003-3240-909X"},"institutions":[{"id":"https://openalex.org/I4210128628","display_name":"Peking University Shenzhen Hospital","ror":"https://ror.org/03kkjyb15","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128628"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingzhi Chen","raw_affiliation_strings":["Peking University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Shenzhen, China","institution_ids":["https://openalex.org/I4210128628"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100602636","display_name":"Yu-xi Liu","orcid":"https://orcid.org/0000-0002-3961-2691"},"institutions":[{"id":"https://openalex.org/I4210128628","display_name":"Peking University Shenzhen Hospital","ror":"https://ror.org/03kkjyb15","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128628"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxi Liu","raw_affiliation_strings":["Peking University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Shenzhen, China","institution_ids":["https://openalex.org/I4210128628"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057015645","display_name":"Guibo Luo","orcid":"https://orcid.org/0000-0002-1709-1207"},"institutions":[{"id":"https://openalex.org/I4210128628","display_name":"Peking University Shenzhen Hospital","ror":"https://ror.org/03kkjyb15","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128628"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guibo Luo","raw_affiliation_strings":["Peking University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Shenzhen, China","institution_ids":["https://openalex.org/I4210128628"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056706680","display_name":"Yuesheng Zhu","orcid":"https://orcid.org/0000-0003-2524-6800"},"institutions":[{"id":"https://openalex.org/I4210128628","display_name":"Peking University Shenzhen Hospital","ror":"https://ror.org/03kkjyb15","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128628"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuesheng Zhu","raw_affiliation_strings":["Peking University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Shenzhen, China","institution_ids":["https://openalex.org/I4210128628"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100332181"],"corresponding_institution_ids":["https://openalex.org/I4210128628"],"apc_list":null,"apc_paid":null,"fwci":1.2784,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.78091642,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"29","issue":"7","first_page":"5042","last_page":"5055"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.8895999789237976,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.8895999789237976,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.8676000237464905,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.8213000297546387,"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/image-segmentation","display_name":"Image segmentation","score":0.6872361302375793},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6525184512138367},{"id":"https://openalex.org/keywords/center","display_name":"Center (category theory)","score":0.6103264689445496},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5878363251686096},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.544727623462677},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5445717573165894},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.5068793892860413},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4958074986934662},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.4663509428501129},{"id":"https://openalex.org/keywords/image-registration","display_name":"Image registration","score":0.45123371481895447},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.42212700843811035},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3736664652824402},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08705002069473267}],"concepts":[{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6872361302375793},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6525184512138367},{"id":"https://openalex.org/C2779463800","wikidata":"https://www.wikidata.org/wiki/Q5062222","display_name":"Center (category theory)","level":2,"score":0.6103264689445496},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5878363251686096},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.544727623462677},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5445717573165894},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.5068793892860413},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4958074986934662},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.4663509428501129},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.45123371481895447},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.42212700843811035},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3736664652824402},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08705002069473267},{"id":"https://openalex.org/C8010536","wikidata":"https://www.wikidata.org/wiki/Q160398","display_name":"Crystallography","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/jbhi.2025.3549029","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2025.3549029","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Biomedical and Health Informatics","raw_type":"journal-article"},{"id":"pmid:40146649","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40146649","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE journal of biomedical and health informatics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1904878066","https://openalex.org/W1974969377","https://openalex.org/W2116612304","https://openalex.org/W2183341477","https://openalex.org/W2535838896","https://openalex.org/W2885343725","https://openalex.org/W2912213068","https://openalex.org/W2919115771","https://openalex.org/W2963073614","https://openalex.org/W2963946669","https://openalex.org/W2964081807","https://openalex.org/W2965658867","https://openalex.org/W2979448322","https://openalex.org/W2979640220","https://openalex.org/W2991040477","https://openalex.org/W3002569343","https://openalex.org/W3014974815","https://openalex.org/W3035014113","https://openalex.org/W3047304572","https://openalex.org/W3091479204","https://openalex.org/W3091870957","https://openalex.org/W3104631511","https://openalex.org/W3127190257","https://openalex.org/W3165215947","https://openalex.org/W3173204563","https://openalex.org/W3176597251","https://openalex.org/W3182158470","https://openalex.org/W3202544039","https://openalex.org/W4229029907","https://openalex.org/W4287332481","https://openalex.org/W4296434131","https://openalex.org/W4299652825","https://openalex.org/W4312707827","https://openalex.org/W4312869277","https://openalex.org/W4312933868","https://openalex.org/W4377107507","https://openalex.org/W4377695098","https://openalex.org/W4387908853","https://openalex.org/W4391806964","https://openalex.org/W4393154185","https://openalex.org/W4403150234","https://openalex.org/W4403840670","https://openalex.org/W6640963894","https://openalex.org/W6728757088","https://openalex.org/W6752029299","https://openalex.org/W6759853437","https://openalex.org/W6762987983","https://openalex.org/W6765541894","https://openalex.org/W6765779288","https://openalex.org/W6773817997","https://openalex.org/W6779823529","https://openalex.org/W6780224944","https://openalex.org/W6797053846","https://openalex.org/W6797359156","https://openalex.org/W6810565495","https://openalex.org/W6849141701","https://openalex.org/W6849315627","https://openalex.org/W6849607646","https://openalex.org/W6857607229","https://openalex.org/W6857950280","https://openalex.org/W6910546390","https://openalex.org/W6991169194"],"related_works":["https://openalex.org/W1986655823","https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W3144569342","https://openalex.org/W3011384228","https://openalex.org/W2124969951","https://openalex.org/W2945274617","https://openalex.org/W4313052709","https://openalex.org/W4298131179","https://openalex.org/W2375430703"],"abstract_inverted_index":{"Learning":[0],"from":[1,130,133],"multi-center":[2,65],"medical":[3,59,221],"datasets":[4,159,222],"to":[5,14,32,55,79,87,100,110,126,201],"obtain":[6],"a":[7,48,57,104,119,148],"high-performance":[8],"global":[9,128],"model":[10,62,76,129,136,154],"is":[11,53,77,108,124,147,190],"challenging":[12],"due":[13],"the":[15,88,112,165,184,212],"privacy":[16,50],"protection":[17],"and":[18,35,40,142,162,207,223],"data":[19,39,90,96,131,170],"heterogeneity":[20],"in":[21,67,227],"healthcare":[22],"systems.":[23],"Current":[24],"federated":[25],"learning":[26],"approaches":[27],"are":[28],"not":[29],"efficient":[30,73],"enough":[31],"learn":[33],"Non-Independent":[34],"Identically":[36],"Distributed":[37],"(Non-IID)":[38],"require":[41],"high":[42],"communication":[43,69,174],"costs.":[44],"In":[45,181],"this":[46,182],"work,":[47],"practical":[49],"computing":[51],"framework":[52,189,217],"proposed":[54,125,188,216],"train":[56],"Non-IID":[58,220],"image":[60],"segmentation":[61,153],"under":[63],"various":[64],"setting":[66,185],"low":[68],"cost.":[70],"Specifically,":[71],"an":[72,172],"cascaded":[74],"diffusion":[75],"trained":[78],"generate":[80],"image-mask":[81,116],"pairs":[82],"that":[83,151],"have":[84],"similar":[85],"distribution":[86],"training":[89],"of":[91,114,121,167,176,186,214],"clients,":[92],"providing":[93,193],"rich":[94],"labeled":[95],"on":[97,156,218,235],"client":[98],"side":[99],"mitigate":[101],"heterogeneity.":[102],"Also,":[103],"label":[105],"construction":[106],"module":[107],"developed":[109],"improve":[111],"quality":[113],"generated":[115,132,158],"pairs.":[117],"Moreover,":[118],"set":[120],"aggregation":[122,195],"methods":[123,196],"achieve":[127],"Cascaded":[134],"Diffusion":[135],"for":[137,204],"diverse":[138],"scenarios:":[139],"CD-Syn,":[140],"CD-Ens":[141,161],"its":[143],"extension":[144],"CD-KD.":[145],"CD-Syn":[146],"one-shot":[149],"method":[150,233],"trains":[152],"solely":[155],"public":[157],"while":[160],"CD-KD":[163],"maximize":[164],"utilization":[166],"local":[168],"original":[169],"by":[171],"extra":[173],"round":[175],"ensemble":[177],"or":[178],"knowledge":[179],"distillation.":[180],"way,":[183],"our":[187,215],"highly":[191],"practical,":[192],"multiple":[194],"which":[197],"can":[198],"flexibly":[199],"adapt":[200],"varying":[202],"demands":[203],"efficiency,":[205],"privacy,":[206],"accuracy.":[208],"We":[209],"systematically":[210],"evaluated":[211],"effectiveness":[213],"five":[219],"observe":[224],"5.38%":[225],"improvement":[226],"Dice":[228],"score":[229],"compared":[230],"with":[231],"baseline":[232],"(FednnU-Net)":[234],"average.":[236]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}