{"id":"https://openalex.org/W4416707387","doi":"https://doi.org/10.1109/jstsp.2025.3637544","title":"SAFFRON: A Physics-Informed, Label-Free Self-Supervised Deep Learning Framework for Fast and Accurate 3D Fetal Brain MRI Reconstruction","display_name":"SAFFRON: A Physics-Informed, Label-Free Self-Supervised Deep Learning Framework for Fast and Accurate 3D Fetal Brain MRI Reconstruction","publication_year":2025,"publication_date":"2025-11-26","ids":{"openalex":"https://openalex.org/W4416707387","doi":"https://doi.org/10.1109/jstsp.2025.3637544"},"language":null,"primary_location":{"id":"doi:10.1109/jstsp.2025.3637544","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2025.3637544","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"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 Selected Topics in Signal Processing","raw_type":"journal-article"},"type":"article","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":null,"display_name":"Jiangjie Wu","orcid":"https://orcid.org/0009-0002-9869-7653"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiangjie Wu","raw_affiliation_strings":["School of Information Science and Technology, ShanghaiTech University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0002-9869-7653","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071936730","display_name":"Taotao Sun","orcid":"https://orcid.org/0000-0002-4103-6902"},"institutions":[{"id":"https://openalex.org/I4210108664","display_name":"International Peace Maternity & Child Health Hospital","ror":"https://ror.org/01byttc20","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210108664"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Taotao Sun","raw_affiliation_strings":["Department of Radiology, International Peace Maternity And Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China","International Peace Maternity, Child Health Hospital, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, International Peace Maternity And Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I4210108664"]},{"raw_affiliation_string":"International Peace Maternity, Child Health Hospital, Shanghai, China","institution_ids":["https://openalex.org/I4210108664"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100434967","display_name":"Lihui Wang","orcid":"https://orcid.org/0000-0002-3558-5112"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]},{"id":"https://openalex.org/I4210109381","display_name":"Affiliated Hospital of Guizhou Medical University","ror":"https://ror.org/02kstas42","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210109381"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lihui Wang","raw_affiliation_strings":["Key Laboratory of Advanced Medical Imaging and Intelligent Computing of Guizhou Province, College of Computer Science and Technology, Guizhou University, Guizhou, China","School of Computer Science and Technology, Guizhou University, Guizhou, China"],"raw_orcid":"https://orcid.org/0000-0002-3558-5112","affiliations":[{"raw_affiliation_string":"Key Laboratory of Advanced Medical Imaging and Intelligent Computing of Guizhou Province, College of Computer Science and Technology, Guizhou University, Guizhou, China","institution_ids":["https://openalex.org/I178232147","https://openalex.org/I4210109381"]},{"raw_affiliation_string":"School of Computer Science and Technology, Guizhou University, Guizhou, China","institution_ids":["https://openalex.org/I178232147"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100654428","display_name":"Yuyao Zhang","orcid":"https://orcid.org/0000-0001-6706-4867"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuyao Zhang","raw_affiliation_strings":["School of Information Science and Technology, ShanghaiTech University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-6706-4867","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"last","author":{"id":null,"display_name":"Hongjiang Wei","orcid":"https://orcid.org/0000-0002-9060-4152"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongjiang Wei","raw_affiliation_strings":["School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-9060-4152","affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I30809798"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.46245935,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"19","issue":"8","first_page":"1955","last_page":"1966"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12552","display_name":"Fetal and Pediatric Neurological Disorders","score":0.9793999791145325,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"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/T12552","display_name":"Fetal and Pediatric Neurological Disorders","score":0.9793999791145325,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.0038999998942017555,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.002300000051036477,"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/deep-learning","display_name":"Deep learning","score":0.6952000260353088},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.5823000073432922},{"id":"https://openalex.org/keywords/3d-reconstruction","display_name":"3D reconstruction","score":0.4242999851703644},{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.41819998621940613},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.38510000705718994},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37619999051094055},{"id":"https://openalex.org/keywords/neuroimaging","display_name":"Neuroimaging","score":0.3637999892234802},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.3504999876022339},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.3467000126838684},{"id":"https://openalex.org/keywords/data-consistency","display_name":"Data consistency","score":0.3449000120162964}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7346000075340271},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7200999855995178},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6952000260353088},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5823000073432922},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5582000017166138},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.4242999851703644},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.41819998621940613},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.38510000705718994},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37619999051094055},{"id":"https://openalex.org/C58693492","wikidata":"https://www.wikidata.org/wiki/Q551875","display_name":"Neuroimaging","level":2,"score":0.3637999892234802},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.3504999876022339},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.3467000126838684},{"id":"https://openalex.org/C93361087","wikidata":"https://www.wikidata.org/wiki/Q4426698","display_name":"Data consistency","level":2,"score":0.3449000120162964},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.34459999203681946},{"id":"https://openalex.org/C157787499","wikidata":"https://www.wikidata.org/wiki/Q13479657","display_name":"Real-time MRI","level":3,"score":0.33309999108314514},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3237999975681305},{"id":"https://openalex.org/C2776863239","wikidata":"https://www.wikidata.org/wiki/Q7936601","display_name":"Visual hull","level":3,"score":0.313400000333786},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.3095000088214874},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.29789999127388},{"id":"https://openalex.org/C2780170424","wikidata":"https://www.wikidata.org/wiki/Q229399","display_name":"3D ultrasound","level":3,"score":0.2969000041484833},{"id":"https://openalex.org/C2779898584","wikidata":"https://www.wikidata.org/wiki/Q7820109","display_name":"Reconstruction algorithm","level":3,"score":0.2879999876022339},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.27950000762939453},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.27649998664855957},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.27459999918937683},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.27250000834465027},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.271699994802475},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.27149999141693115},{"id":"https://openalex.org/C128840427","wikidata":"https://www.wikidata.org/wiki/Q1302174","display_name":"Motion compensation","level":2,"score":0.2685000002384186},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.26109999418258667},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2572999894618988},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25380000472068787}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jstsp.2025.3637544","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2025.3637544","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"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 Selected Topics in Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4223832560","display_name":null,"funder_award_id":"62571328","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"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W242464784","https://openalex.org/W1891734390","https://openalex.org/W1994514622","https://openalex.org/W2024251722","https://openalex.org/W2032492890","https://openalex.org/W2085681975","https://openalex.org/W2090612612","https://openalex.org/W2117340355","https://openalex.org/W2135264048","https://openalex.org/W2138621273","https://openalex.org/W2156875969","https://openalex.org/W2166966312","https://openalex.org/W2194775991","https://openalex.org/W2442117232","https://openalex.org/W2549627956","https://openalex.org/W2591825272","https://openalex.org/W2594602134","https://openalex.org/W2600904149","https://openalex.org/W2604388535","https://openalex.org/W2611467245","https://openalex.org/W2766975021","https://openalex.org/W2950564960","https://openalex.org/W2956625312","https://openalex.org/W2963542386","https://openalex.org/W2975527920","https://openalex.org/W2989249732","https://openalex.org/W3008496132","https://openalex.org/W3012412627","https://openalex.org/W3039236647","https://openalex.org/W3101204238","https://openalex.org/W3131178947","https://openalex.org/W3157453674","https://openalex.org/W3165593106","https://openalex.org/W3165879214","https://openalex.org/W3183422592","https://openalex.org/W3203313349","https://openalex.org/W4280530093","https://openalex.org/W4283382342","https://openalex.org/W4285388993","https://openalex.org/W4315630735","https://openalex.org/W4318755798","https://openalex.org/W4385245566","https://openalex.org/W4385637995","https://openalex.org/W4386350531","https://openalex.org/W4387623857","https://openalex.org/W4389665200","https://openalex.org/W4406808149"],"related_works":[],"abstract_inverted_index":{"Fetal":[0],"brain":[1,80,109],"MRI":[2,110],"has":[3],"become":[4],"indispensable":[5],"in":[6,66,222],"prenatal":[7],"diagnosis,":[8],"offering":[9],"unique":[10],"soft":[11],"tissue":[12],"contrast":[13],"to":[14,41,182,192,218],"evaluate":[15],"cortical":[16],"development":[17],"and":[18,45,57,105,133,159,187,201],"detect":[19],"neurological":[20],"abnormalities.":[21],"While":[22],"high-resolution":[23],"3D":[24,78,107,118,161],"imaging":[25],"can":[26],"provide":[27],"valuable":[28],"anatomical":[29],"information,":[30],"clinical":[31,68,202],"acquisitions":[32],"are":[33,54],"often":[34],"inadequate":[35],"for":[36,103,116],"reliable":[37],"volumetric":[38],"reconstruction":[39,50,89,137,163,213],"due":[40],"unpredictable":[42],"fetal":[43,79,108],"motion":[44,61,146],"thick-slice":[46],"protocols.":[47],"Conventional":[48],"iterative":[49],"methods,":[51,210],"though":[52],"effective,":[53],"computationally":[55],"intensive":[56],"struggle":[58],"with":[59,126],"severe":[60],"artifacts,":[62],"limiting":[63],"their":[64],"feasibility":[65],"fast-paced":[67],"workflows.":[69],"At":[70],"the":[71,74,114],"same":[72],"time,":[73],"scarcity":[75],"of":[76],"authentic":[77],"volumes":[81,119],"prevents":[82],"supervised":[83],"learning":[84],"approaches":[85],"from":[86],"developing":[87],"generalizable":[88],"models.":[90],"To":[91],"overcome":[92],"these":[93],"limitations,":[94],"we":[95],"introduce":[96],"SAFFRON,":[97],"a":[98,156,177,188,219],"physics-informed,":[99],"label-free":[100],"self-supervised":[101],"framework":[102],"efficient":[104],"high-fidelity":[106],"reconstruction.":[111],"SAFFRON":[112,206],"eliminates":[113],"need":[115],"ground-truth":[117],"by":[120,173],"combining":[121],"physics-driven":[122],"slice":[123],"acquisition":[124],"modeling":[125],"data-driven":[127],"deep":[128],"learning,":[129],"thereby":[130],"bridging":[131],"model-based":[132],"learning-based":[134],"paradigms.":[135],"The":[136],"task":[138],"is":[139,170],"decomposed":[140],"into":[141,155],"two":[142,174],"modules:":[143],"(1)":[144],"multi-stack":[145],"estimation":[147],"via":[148,164],"an":[149,165],"SVR":[150],"network":[151],"that":[152,205],"aligns":[153],"slices":[154],"canonical":[157],"space,":[158],"(2)":[160],"volume":[162],"SRR":[166],"network.":[167],"Reconstruction":[168],"quality":[169],"further":[171],"enhanced":[172],"targeted":[175],"constraints:":[176],"stack-level":[178],"contextual":[179],"consistency":[180],"loss":[181,191],"guide":[183],"more":[184],"accurate":[185],"alignment":[186],"slice-level":[189],"adversarial":[190],"promote":[193],"anatomically":[194],"realistic":[195],"structures.":[196],"Extensive":[197],"experiments":[198],"on":[199],"simulated":[200],"datasets":[203],"demonstrate":[204],"substantially":[207],"outperforms":[208],"state-of-the-art":[209],"achieving":[211],"superior":[212],"accuracy":[214],"while":[215],"delivering":[216],"up":[217],"60\u00d7":[220],"acceleration":[221],"processing":[223],"speed.":[224]},"counts_by_year":[],"updated_date":"2026-04-25T08:17:42.794288","created_date":"2025-11-27T00:00:00"}