{"id":"https://openalex.org/W4386523797","doi":"https://doi.org/10.1109/jbhi.2023.3312748","title":"Cross-Domain Unpaired Learning for Low-Dose CT Imaging","display_name":"Cross-Domain Unpaired Learning for Low-Dose CT Imaging","publication_year":2023,"publication_date":"2023-09-07","ids":{"openalex":"https://openalex.org/W4386523797","doi":"https://doi.org/10.1109/jbhi.2023.3312748","pmid":"https://pubmed.ncbi.nlm.nih.gov/37676796"},"language":"en","primary_location":{"id":"doi:10.1109/jbhi.2023.3312748","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2023.3312748","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/A5045356485","display_name":"Yang Liu","orcid":"https://orcid.org/0000-0002-9159-9252"},"institutions":[{"id":"https://openalex.org/I92039509","display_name":"Guangzhou Medical University","ror":"https://ror.org/00zat6v61","country_code":"CN","type":"education","lineage":["https://openalex.org/I92039509"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yang Liu","raw_affiliation_strings":["Sixth Affiliated Hospital, Guangzhou Medical University, Qingyuan, China","School of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-9159-9252","affiliations":[{"raw_affiliation_string":"Sixth Affiliated Hospital, Guangzhou Medical University, Qingyuan, China","institution_ids":["https://openalex.org/I92039509"]},{"raw_affiliation_string":"School of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China","institution_ids":["https://openalex.org/I92039509"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102751108","display_name":"Gaofeng Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I4210097354","display_name":"Sun Yat-sen Memorial Hospital","ror":"https://ror.org/01px77p81","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210097354"]},{"id":"https://openalex.org/I92039509","display_name":"Guangzhou Medical University","ror":"https://ror.org/00zat6v61","country_code":"CN","type":"education","lineage":["https://openalex.org/I92039509"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gaofeng Chen","raw_affiliation_strings":["School of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China","Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0005-0916-0777","affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China","institution_ids":["https://openalex.org/I92039509"]},{"raw_affiliation_string":"Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I4210097354","https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066091439","display_name":"Shumao Pang","orcid":"https://orcid.org/0000-0003-0409-8562"},"institutions":[{"id":"https://openalex.org/I92039509","display_name":"Guangzhou Medical University","ror":"https://ror.org/00zat6v61","country_code":"CN","type":"education","lineage":["https://openalex.org/I92039509"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shumao Pang","raw_affiliation_strings":["School of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-0409-8562","affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China","institution_ids":["https://openalex.org/I92039509"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100613149","display_name":"Dong Zeng","orcid":"https://orcid.org/0000-0001-6015-5010"},"institutions":[{"id":"https://openalex.org/I58200834","display_name":"Southern Medical University","ror":"https://ror.org/01vjw4z39","country_code":"CN","type":"education","lineage":["https://openalex.org/I58200834"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Zeng","raw_affiliation_strings":["School of Biomedical Engineering, Southern Medical University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-6015-5010","affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Southern Medical University, Guangzhou, China","institution_ids":["https://openalex.org/I58200834"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024327683","display_name":"Youde Ding","orcid":"https://orcid.org/0000-0001-8973-098X"},"institutions":[{"id":"https://openalex.org/I92039509","display_name":"Guangzhou Medical University","ror":"https://ror.org/00zat6v61","country_code":"CN","type":"education","lineage":["https://openalex.org/I92039509"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youde Ding","raw_affiliation_strings":["Sixth Affiliated Hospital, Guangzhou Medical University, Qingyuan, China","School of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-8973-098X","affiliations":[{"raw_affiliation_string":"Sixth Affiliated Hospital, Guangzhou Medical University, Qingyuan, China","institution_ids":["https://openalex.org/I92039509"]},{"raw_affiliation_string":"School of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China","institution_ids":["https://openalex.org/I92039509"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001623259","display_name":"Guoxi Xie","orcid":"https://orcid.org/0000-0002-4842-7252"},"institutions":[{"id":"https://openalex.org/I92039509","display_name":"Guangzhou Medical University","ror":"https://ror.org/00zat6v61","country_code":"CN","type":"education","lineage":["https://openalex.org/I92039509"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoxi Xie","raw_affiliation_strings":["School of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-4842-7252","affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China","institution_ids":["https://openalex.org/I92039509"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006049117","display_name":"Jianhua Ma","orcid":"https://orcid.org/0000-0003-2958-1710"},"institutions":[{"id":"https://openalex.org/I58200834","display_name":"Southern Medical University","ror":"https://ror.org/01vjw4z39","country_code":"CN","type":"education","lineage":["https://openalex.org/I58200834"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianhua Ma","raw_affiliation_strings":["School of Biomedical Engineering, Southern Medical University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-2958-1710","affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Southern Medical University, Guangzhou, China","institution_ids":["https://openalex.org/I58200834"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017295309","display_name":"Ji He","orcid":"https://orcid.org/0000-0001-9811-6500"},"institutions":[{"id":"https://openalex.org/I92039509","display_name":"Guangzhou Medical University","ror":"https://ror.org/00zat6v61","country_code":"CN","type":"education","lineage":["https://openalex.org/I92039509"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ji He","raw_affiliation_strings":["School of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-9811-6500","affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China","institution_ids":["https://openalex.org/I92039509"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5045356485"],"corresponding_institution_ids":["https://openalex.org/I92039509"],"apc_list":null,"apc_paid":null,"fwci":2.684,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.90364576,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"27","issue":"11","first_page":"5471","last_page":"5482"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9997000098228455,"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"}},{"id":"https://openalex.org/T10844","display_name":"Radiation Dose and Imaging","score":0.9980999827384949,"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/computer-science","display_name":"Computer science","score":0.7357016801834106},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.723670244216919},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6552735567092896},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6070538759231567},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.5027830600738525},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.49207037687301636},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47185182571411133},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46983999013900757},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4609992504119873},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.447252094745636},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08578541874885559}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7357016801834106},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.723670244216919},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6552735567092896},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6070538759231567},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.5027830600738525},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.49207037687301636},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47185182571411133},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46983999013900757},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4609992504119873},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.447252094745636},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08578541874885559},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"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":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D059629","descriptor_name":"Signal-To-Noise Ratio","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D059629","descriptor_name":"Signal-To-Noise Ratio","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D059629","descriptor_name":"Signal-To-Noise Ratio","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/jbhi.2023.3312748","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2023.3312748","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:37676796","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37676796","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":[{"id":"https://openalex.org/G2147306347","display_name":null,"funder_award_id":"62001207","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4294587151","display_name":null,"funder_award_id":"62001208","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7326078524","display_name":null,"funder_award_id":"U1708261","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8698885527","display_name":null,"funder_award_id":"U21A6005","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1996293545","https://openalex.org/W2064526599","https://openalex.org/W2133665775","https://openalex.org/W2171697262","https://openalex.org/W2319126251","https://openalex.org/W2469946482","https://openalex.org/W2508457857","https://openalex.org/W2764207251","https://openalex.org/W2766327008","https://openalex.org/W2793146153","https://openalex.org/W2798278116","https://openalex.org/W2887372463","https://openalex.org/W2911290743","https://openalex.org/W2946539594","https://openalex.org/W2963684088","https://openalex.org/W2968087827","https://openalex.org/W2992095291","https://openalex.org/W2997053073","https://openalex.org/W3011790227","https://openalex.org/W3080821159","https://openalex.org/W3089733083","https://openalex.org/W3099334623","https://openalex.org/W3111841671","https://openalex.org/W3112965401","https://openalex.org/W3119395232","https://openalex.org/W3154224604","https://openalex.org/W3212800953","https://openalex.org/W3216209061","https://openalex.org/W3216826802","https://openalex.org/W4290715421","https://openalex.org/W4295521014","https://openalex.org/W4319452907","https://openalex.org/W4386075565","https://openalex.org/W4390872720","https://openalex.org/W6685352114","https://openalex.org/W6735913928","https://openalex.org/W6749271710","https://openalex.org/W6753612573","https://openalex.org/W6759001153","https://openalex.org/W6809940947","https://openalex.org/W6849519549"],"related_works":["https://openalex.org/W2366107444","https://openalex.org/W4388145910","https://openalex.org/W2990774877","https://openalex.org/W3024479225","https://openalex.org/W3171371563","https://openalex.org/W2995680918","https://openalex.org/W3093339210","https://openalex.org/W3133954817","https://openalex.org/W3003847115","https://openalex.org/W3015037427"],"abstract_inverted_index":{"Supervised":[0],"deep-learning":[1,40,70],"techniques":[2,41,71],"with":[3,17],"paired":[4,22,57,86,113,173],"training":[5,23,58,82,87,114],"datasets":[6,24,197],"have":[7],"been":[8],"widely":[9,63],"studied":[10],"for":[11,75,129],"low-dose":[12],"computed":[13],"tomography":[14],"(LDCT)":[15],"imaging":[16,79,211],"excellent":[18],"performance.":[19],"However,":[20,89],"the":[21,35,62,77,84,92,100,111,160,168,178,190,193,204],"are":[25,103,198],"usually":[26],"difficult":[27,104],"to":[28,53,91,105,109,181],"obtain":[29,208],"in":[30,42,97,107,159,167,177,213],"clinical":[31,43,196],"routine,":[32],"which":[33,138],"restricts":[34],"wide":[36],"adoption":[37],"of":[38,94,166,192],"supervised":[39,69],"practices.":[44],"To":[45,188],"address":[46],"this":[47,117],"issue,":[48],"a":[49,55,121,144,155,171],"general":[50],"idea":[51],"is":[52,139,151,175],"construct":[54,110],"pseudo":[56,85,112,130,146,172],"dataset":[59,174],"based":[60,153],"on":[61,83,154],"available":[64],"unpaired":[65,126],"data,":[66],"after":[67],"which,":[68],"can":[72,207],"be":[73],"adopted":[74],"improving":[76],"LDCT":[78,101,131,135,147,184,210],"performance":[80,212],"by":[81],"dataset.":[88,115],"due":[90],"complexity":[93],"noise":[95,157],"properties":[96],"CT":[98],"imaging,":[99],"data":[102,132],"generate":[106],"order":[108],"In":[116],"article,":[118],"we":[119],"propose":[120],"simple":[122],"yet":[123],"effective":[124],"cross-domain":[125],"learning":[127],"framework":[128,206],"generation":[133],"and":[134,163,216],"image":[136,179,185],"reconstruction,":[137],"denoted":[140],"as":[141],"CrossDuL.":[142],"Specifically,":[143],"dedicated":[145],"sinogram":[148,161,169],"generative":[149],"module":[150],"constructed":[152,176],"data-dependent":[156],"model":[158],"domain,":[162,170],"then":[164],"instead":[165],"domain":[180],"train":[182],"an":[183],"restoration":[186],"module.":[187],"validate":[189],"effectiveness":[191],"proposed":[194],"framework,":[195],"adopted.":[199],"Experimental":[200],"results":[201],"demonstrate":[202],"that":[203],"CrossDuL":[205],"promising":[209],"both":[214],"quantitative":[215],"qualitative":[217],"measurements.":[218]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
