{"id":"https://openalex.org/W4413104873","doi":"https://doi.org/10.1109/tmi.2025.3597401","title":"An Unsupervised Learning Approach for Reconstructing 3T-Like Images From 0.3T MRI Without Paired Training Data","display_name":"An Unsupervised Learning Approach for Reconstructing 3T-Like Images From 0.3T MRI Without Paired Training Data","publication_year":2025,"publication_date":"2025-08-11","ids":{"openalex":"https://openalex.org/W4413104873","doi":"https://doi.org/10.1109/tmi.2025.3597401","pmid":"https://pubmed.ncbi.nlm.nih.gov/40788786"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2025.3597401","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2025.3597401","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"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 Transactions on Medical Imaging","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/A5085985501","display_name":"Huaishui Yang","orcid":"https://orcid.org/0009-0001-1656-9336"},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Huaishui Yang","raw_affiliation_strings":["College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China","institution_ids":["https://openalex.org/I4210152380"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100616225","display_name":"Shaojun Liu","orcid":"https://orcid.org/0000-0002-9201-9301"},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaojun Liu","raw_affiliation_strings":["College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China","institution_ids":["https://openalex.org/I4210152380"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100638607","display_name":"Yilong Liu","orcid":"https://orcid.org/0000-0001-9295-7982"},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yilong Liu","raw_affiliation_strings":["Guangdong-Hongkong-Macau Institute of CNS Regeneration, Key Laboratory of CNS Regeneration (Ministry of Education), Jinan University, Guangzhou, China","Key Laboratory of CNS Regeneration (Ministry of Education), Guangdong-Hongkong-Macau Institute of CNS Regeneration, Jinan University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Guangdong-Hongkong-Macau Institute of CNS Regeneration, Key Laboratory of CNS Regeneration (Ministry of Education), Jinan University, Guangzhou, China","institution_ids":["https://openalex.org/I159948400"]},{"raw_affiliation_string":"Key Laboratory of CNS Regeneration (Ministry of Education), Guangdong-Hongkong-Macau Institute of CNS Regeneration, Jinan University, Guangzhou, China","institution_ids":["https://openalex.org/I159948400"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030354218","display_name":"Lingyan Zhang","orcid":"https://orcid.org/0009-0001-6613-252X"},"institutions":[{"id":"https://openalex.org/I4210092654","display_name":"Longgang Central Hospital","ror":"https://ror.org/00j5y7k81","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210092654"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingyan Zhang","raw_affiliation_strings":["Department of Radiology, Longgang Central Hospital of Shenzhen (Shenzhen Clinical Medical College, Lab of Molecular Imaging and Medical Intelligence, Guangzhou University of Chinese Medicine; Longgang Clinical Institute of Shantou University Medical College), Shenzhen, China","Department of Radiology, Lab of Molecular Imaging and Medical Intelligence, Longgang Central Hospital of Shenzhen (Shenzhen Clinical Medical College, Guangzhou University of Chinese MedicineLonggang Clinical Institute of Shantou University Medical College), Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, Longgang Central Hospital of Shenzhen (Shenzhen Clinical Medical College, Lab of Molecular Imaging and Medical Intelligence, Guangzhou University of Chinese Medicine; Longgang Clinical Institute of Shantou University Medical College), Shenzhen, China","institution_ids":["https://openalex.org/I4210092654"]},{"raw_affiliation_string":"Department of Radiology, Lab of Molecular Imaging and Medical Intelligence, Longgang Central Hospital of Shenzhen (Shenzhen Clinical Medical College, Guangzhou University of Chinese MedicineLonggang Clinical Institute of Shantou University Medical College), Shenzhen, China","institution_ids":["https://openalex.org/I4210092654"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038210831","display_name":"Shoujin Huang","orcid":"https://orcid.org/0000-0001-6094-129X"},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shoujin Huang","raw_affiliation_strings":["College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China","institution_ids":["https://openalex.org/I4210152380"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101085193","display_name":"Jiayu Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiayu Zheng","raw_affiliation_strings":["College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China","institution_ids":["https://openalex.org/I4210152380"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052178126","display_name":"Jingzhe Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210155055","display_name":"Beijing Hua Xin Hospital","ror":"https://ror.org/04k6zqn86","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210155055"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingzhe Liu","raw_affiliation_strings":["Department of Radiology, The First Hospital of Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, The First Hospital of Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I4210155055"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085884394","display_name":"Hua Guo","orcid":"https://orcid.org/0000-0002-0482-1493"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hua Guo","raw_affiliation_strings":["Department of Biomedical Engineering, School of Medicine, Center for Biomedical Imaging Research, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, School of Medicine, Center for Biomedical Imaging Research, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047512270","display_name":"EX Wu","orcid":"https://orcid.org/0000-0001-5581-1546"},"institutions":[{"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":["HK"],"is_corresponding":false,"raw_author_name":"Ed X. Wu","raw_affiliation_strings":["Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong, China","Laboratory of Biomedical Imaging and Signal Processing, University of Hong Kong, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I889458895"]},{"raw_affiliation_string":"Laboratory of Biomedical Imaging and Signal Processing, University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008625474","display_name":"Mengye Lyu","orcid":"https://orcid.org/0000-0001-5548-8136"},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengye Lyu","raw_affiliation_strings":["College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China","institution_ids":["https://openalex.org/I4210152380"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":10,"corresponding_author_ids":["https://openalex.org/A5085985501"],"corresponding_institution_ids":["https://openalex.org/I4210152380"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28436676,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"44","issue":"12","first_page":"5358","last_page":"5371"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9477999806404114,"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/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9477999806404114,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9372000098228455,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9355000257492065,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.706933856010437},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6168361902236938},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5469563007354736},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.46443140506744385},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.45608824491500854},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.4471127688884735},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.44543930888175964},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4311065375804901},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4221242368221283}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.706933856010437},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6168361902236938},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5469563007354736},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.46443140506744385},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.45608824491500854},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.4471127688884735},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.44543930888175964},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4311065375804901},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4221242368221283},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000069558","descriptor_name":"Unsupervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069558","descriptor_name":"Unsupervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069558","descriptor_name":"Unsupervised Machine 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":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":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","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":"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":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":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/tmi.2025.3597401","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2025.3597401","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"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 Transactions on Medical Imaging","raw_type":"journal-article"},{"id":"pmid:40788786","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40788786","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 transactions on medical imaging","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4796736575","display_name":null,"funder_award_id":"20200208","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5368654448","display_name":null,"funder_award_id":"GDRC202117","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6324129832","display_name":null,"funder_award_id":"62101348","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7418875311","display_name":null,"funder_award_id":"62301332","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":73,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1975051506","https://openalex.org/W2005503451","https://openalex.org/W2020519533","https://openalex.org/W2056370875","https://openalex.org/W2133127325","https://openalex.org/W2133665775","https://openalex.org/W2139209606","https://openalex.org/W2151707108","https://openalex.org/W2331918145","https://openalex.org/W2587341032","https://openalex.org/W2743780012","https://openalex.org/W2890422129","https://openalex.org/W2910728592","https://openalex.org/W2911060328","https://openalex.org/W2914057844","https://openalex.org/W2927933146","https://openalex.org/W2950689937","https://openalex.org/W2962785568","https://openalex.org/W2962793481","https://openalex.org/W2963073614","https://openalex.org/W2963768110","https://openalex.org/W2963869863","https://openalex.org/W2966737464","https://openalex.org/W2977860782","https://openalex.org/W2978074392","https://openalex.org/W2979652095","https://openalex.org/W2982362131","https://openalex.org/W3001554227","https://openalex.org/W3006755272","https://openalex.org/W3092635044","https://openalex.org/W3116694041","https://openalex.org/W3122406287","https://openalex.org/W3154672809","https://openalex.org/W3164353984","https://openalex.org/W3169097848","https://openalex.org/W3171838928","https://openalex.org/W3185466076","https://openalex.org/W3194713134","https://openalex.org/W3195279129","https://openalex.org/W3196878101","https://openalex.org/W3203682406","https://openalex.org/W3203913839","https://openalex.org/W4200575161","https://openalex.org/W4205227112","https://openalex.org/W4296268709","https://openalex.org/W4312938066","https://openalex.org/W4313524971","https://openalex.org/W4362506979","https://openalex.org/W4366822967","https://openalex.org/W4372342314","https://openalex.org/W4376133665","https://openalex.org/W4379515561","https://openalex.org/W4382372079","https://openalex.org/W4383059059","https://openalex.org/W4384561848","https://openalex.org/W4385309150","https://openalex.org/W4385792358","https://openalex.org/W4386952044","https://openalex.org/W4386972913","https://openalex.org/W4387211174","https://openalex.org/W4387211280","https://openalex.org/W4389225575","https://openalex.org/W4390400361","https://openalex.org/W4392114275","https://openalex.org/W4392698312","https://openalex.org/W4393305452","https://openalex.org/W4399131865","https://openalex.org/W4403069559","https://openalex.org/W4403069605","https://openalex.org/W4403071391","https://openalex.org/W4403174193","https://openalex.org/W4403204363"],"related_works":["https://openalex.org/W230091440","https://openalex.org/W2233261550","https://openalex.org/W2810751659","https://openalex.org/W258997015","https://openalex.org/W2997094352","https://openalex.org/W4412817058","https://openalex.org/W3216976533","https://openalex.org/W100620283","https://openalex.org/W4394050964","https://openalex.org/W2551249631"],"abstract_inverted_index":{"Magnetic":[0],"resonance":[1],"imaging":[2],"(MRI)":[3],"is":[4,113],"powerful":[5],"in":[6,32,145],"medical":[7],"diagnostics,":[8],"yet":[9],"high-field":[10],"MRI,":[11],"despite":[12],"offering":[13],"superior":[14],"image":[15],"quality,":[16],"incurs":[17],"significant":[18],"costs":[19],"for":[20,65],"procurement,":[21],"installation,":[22],"maintenance,":[23],"and":[24,29,34,95,120,135,148],"operation,":[25],"restricting":[26],"its":[27],"availability":[28],"accessibility,":[30],"especially":[31],"low-":[33],"middle-income":[35],"countries.":[36],"Addressing":[37],"this,":[38],"our":[39],"study":[40],"proposes":[41],"an":[42,82,97],"unsupervised":[43,168],"learning":[44],"algorithm":[45],"based":[46],"on":[47,115,123],"cycle-consistent":[48],"generative":[49,111],"adversarial":[50],"networks.":[51],"This":[52,155],"framework":[53],"transforms":[54],"0.3T":[55],"low-field":[56,93,179],"MRI":[57,131,163],"into":[58],"higher-quality":[59],"3T-like":[60],"images,":[61],"bypassing":[62],"the":[63,91,176],"need":[64],"paired":[66,124],"low/high-field":[67,125],"training":[68],"data.":[69],"The":[70,109],"proposed":[71,110],"architecture":[72],"integrates":[73],"two":[74],"novel":[75],"modules":[76],"to":[77,174],"enhance":[78,175],"reconstruction":[79],"quality:":[80],"(1)":[81],"attention":[83],"block":[84,99],"that":[85,100,170],"dynamically":[86],"balances":[87],"high-field-like":[88],"features":[89],"with":[90],"original":[92],"input,":[94],"(2)":[96],"edge":[98],"refines":[101],"boundary":[102],"details,":[103],"providing":[104,165],"more":[105],"accurate":[106],"structural":[107],"reconstruction.":[108],"model":[112],"trained":[114],"large-scale,":[116],"unpaired,":[117],"public":[118],"datasets,":[119],"further":[121],"validated":[122],"acquisitions":[126],"of":[127,178],"three":[128],"major":[129],"clinical":[130],"sequences:":[132],"T1-weighted,":[133],"T2-weighted,":[134],"fluid-attenuated":[136],"inversion":[137],"recovery":[138],"(FLAIR)":[139],"imaging.":[140],"It":[141],"demonstrates":[142],"notable":[143],"improvements":[144],"tissue":[146],"contrast":[147],"signal-to-noise":[149],"ratio":[150],"while":[151],"preserving":[152],"anatomical":[153],"fidelity.":[154],"approach":[156],"utilizes":[157],"rich":[158],"information":[159],"from":[160],"publicly":[161],"available":[162],"resources,":[164],"a":[166],"data-efficient":[167],"alternative":[169],"complements":[171],"supervised":[172],"methods":[173],"utility":[177],"MRI.":[180]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}