{"id":"https://openalex.org/W7123356221","doi":"https://doi.org/10.1109/tii.2025.3642293","title":"Unsupervised Sensitivity Prior Generation With Diffusion Model for EIT Image Reconstruction","display_name":"Unsupervised Sensitivity Prior Generation With Diffusion Model for EIT Image Reconstruction","publication_year":2026,"publication_date":"2026-01-12","ids":{"openalex":"https://openalex.org/W7123356221","doi":"https://doi.org/10.1109/tii.2025.3642293"},"language":null,"primary_location":{"id":"doi:10.1109/tii.2025.3642293","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2025.3642293","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","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":"https://openalex.org/A5100784335","display_name":"Zichen Wang","orcid":"https://orcid.org/0000-0001-8940-6792"},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zichen Wang","raw_affiliation_strings":["School of Electronic and Information Engineering, Tiangong University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0001-8940-6792","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Tiangong University, Tianjin, China","institution_ids":["https://openalex.org/I198091727"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122848919","display_name":"Tao Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Zhang","raw_affiliation_strings":["School of Electronic and Information Engineering, Tiangong University, Tianjin, China"],"raw_orcid":"https://orcid.org/0009-0007-6457-0765","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Tiangong University, Tianjin, China","institution_ids":["https://openalex.org/I198091727"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122892992","display_name":"Xinyu Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I17301866","display_name":"University of Alabama","ror":"https://ror.org/03xrrjk67","country_code":"US","type":"education","lineage":["https://openalex.org/I17301866"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinyu Zhang","raw_affiliation_strings":["Department of Computer Science, The University of Alabama, Tuscaloosa, AL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Alabama, Tuscaloosa, AL, USA","institution_ids":["https://openalex.org/I17301866"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001135373","display_name":"Rong Fu","orcid":"https://orcid.org/0000-0002-4946-0329"},"institutions":[{"id":"https://openalex.org/I17301866","display_name":"University of Alabama","ror":"https://ror.org/03xrrjk67","country_code":"US","type":"education","lineage":["https://openalex.org/I17301866"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rong Fu","raw_affiliation_strings":["Department of electrical and computer engineering, The University of Alabama, Tuscaloosa, AL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of electrical and computer engineering, The University of Alabama, Tuscaloosa, AL, USA","institution_ids":["https://openalex.org/I17301866"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122871819","display_name":"Daniel de la Calle","orcid":null},"institutions":[{"id":"https://openalex.org/I17301866","display_name":"University of Alabama","ror":"https://ror.org/03xrrjk67","country_code":"US","type":"education","lineage":["https://openalex.org/I17301866"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel de la Calle","raw_affiliation_strings":["Department of Computer Science, The University of Alabama, Tuscaloosa, AL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Alabama, Tuscaloosa, AL, USA","institution_ids":["https://openalex.org/I17301866"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122856422","display_name":"Chi-Sheng Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I1316535847","display_name":"Beth Israel Deaconess Medical Center","ror":"https://ror.org/04drvxt59","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1316535847"]},{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chi-Sheng Chen","raw_affiliation_strings":["Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA","institution_ids":["https://openalex.org/I1316535847","https://openalex.org/I136199984"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Augustine E Loshelder","orcid":null},"institutions":[{"id":"https://openalex.org/I17301866","display_name":"University of Alabama","ror":"https://ror.org/03xrrjk67","country_code":"US","type":"education","lineage":["https://openalex.org/I17301866"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Augustine E Loshelder","raw_affiliation_strings":["Department of Aerospace Engineering, The University of Alabama, Tuscaloosa, AL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Aerospace Engineering, The University of Alabama, Tuscaloosa, AL, USA","institution_ids":["https://openalex.org/I17301866"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122851217","display_name":"Xiaoyan Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I132369690","display_name":"Tianjin University of Science and Technology","ror":"https://ror.org/018rbtf37","country_code":"CN","type":"education","lineage":["https://openalex.org/I132369690"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyan Chen","raw_affiliation_strings":["College of Electronic Information and Automatic, Tianjin University of Science and Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-4456-660X","affiliations":[{"raw_affiliation_string":"College of Electronic Information and Automatic, Tianjin University of Science and Technology, Tianjin, China","institution_ids":["https://openalex.org/I132369690"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5122881179","display_name":"Qi Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Wang","raw_affiliation_strings":["School of Electronic and Information Engineering, Tiangong University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-5339-5427","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Tiangong University, Tianjin, China","institution_ids":["https://openalex.org/I198091727"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.2519,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.85910892,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"22","issue":"4","first_page":"3400","last_page":"3411"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11778","display_name":"Electrical and Bioimpedance Tomography","score":0.9800000190734863,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11778","display_name":"Electrical and Bioimpedance Tomography","score":0.9800000190734863,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.00800000037997961,"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/T11205","display_name":"Numerical methods in inverse problems","score":0.002899999963119626,"subfield":{"id":"https://openalex.org/subfields/2610","display_name":"Mathematical Physics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.603600025177002},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.5879999995231628},{"id":"https://openalex.org/keywords/electrical-impedance-tomography","display_name":"Electrical impedance tomography","score":0.5120999813079834},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.48190000653266907},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4595000147819519},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.459199994802475},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.40880000591278076},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.40849998593330383},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.39500001072883606}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6632999777793884},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6380000114440918},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.603600025177002},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.5879999995231628},{"id":"https://openalex.org/C155175808","wikidata":"https://www.wikidata.org/wiki/Q1326472","display_name":"Electrical impedance tomography","level":3,"score":0.5120999813079834},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.48190000653266907},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4595000147819519},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.459199994802475},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4341000020503998},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41190001368522644},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.40880000591278076},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.40849998593330383},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.39500001072883606},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39259999990463257},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.38260000944137573},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.3407999873161316},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.33660000562667847},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.328000009059906},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3264999985694885},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.32420000433921814},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.3188999891281128},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.3156000077724457},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.3043999969959259},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.273499995470047},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2671000063419342},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.26019999384880066}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tii.2025.3642293","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2025.3642293","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals","score":0.42300206422805786}],"awards":[{"id":"https://openalex.org/G1848351460","display_name":null,"funder_award_id":"62071328","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4851529722","display_name":null,"funder_award_id":"61903273","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6948971276","display_name":null,"funder_award_id":"62072335","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6998032734","display_name":null,"funder_award_id":"61872269","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":34,"referenced_works":["https://openalex.org/W2342572800","https://openalex.org/W2594988164","https://openalex.org/W2767248316","https://openalex.org/W2990050904","https://openalex.org/W2999516274","https://openalex.org/W3039679801","https://openalex.org/W3047238636","https://openalex.org/W3138808092","https://openalex.org/W3161947941","https://openalex.org/W3194523157","https://openalex.org/W3209243150","https://openalex.org/W4200480062","https://openalex.org/W4293242669","https://openalex.org/W4294691181","https://openalex.org/W4319986922","https://openalex.org/W4386737326","https://openalex.org/W4390357664","https://openalex.org/W4390483633","https://openalex.org/W4391533500","https://openalex.org/W4392309076","https://openalex.org/W4392973923","https://openalex.org/W4393148721","https://openalex.org/W4393252887","https://openalex.org/W4398138244","https://openalex.org/W4403021881","https://openalex.org/W4403094601","https://openalex.org/W4403279377","https://openalex.org/W4403674696","https://openalex.org/W4404952039","https://openalex.org/W4407900684","https://openalex.org/W4408145480","https://openalex.org/W4408325111","https://openalex.org/W4409326045","https://openalex.org/W4411920968"],"related_works":[],"abstract_inverted_index":{"The":[0,19,71,187],"supervised":[1],"deep":[2],"learning":[3],"methods":[4,179],"for":[5,23,54],"electrical":[6,38],"impedance":[7],"tomography":[8],"(EIT)":[9],"remains":[10],"limited":[11],"by":[12,84],"hand-crafted":[13],"and":[14,112,167,176,185,189],"domain-specific":[15],"instructions":[16],"during":[17],"training.":[18],"existing":[20],"unsupervised":[21,46],"solvers":[22],"EIT":[24,68],"trade":[25],"attention":[26],"to":[27,33,51,66,79,89,117,131],"the":[28,37,63,109,125,146],"image":[29,154],"domain":[30],"with":[31],"ignorance":[32],"physical":[34],"natures":[35],"in":[36,180],"field.":[39],"In":[40,93,123],"this":[41],"article,":[42],"we":[43,95],"propose":[44,96],"an":[45],"conditional":[47,72],"diffusion":[48,73],"model,":[49],"referred":[50],"as":[52,62,150,152],"SPfusion,":[53,94],"inhomogeneous":[55,147],"sensitivity":[56,104,148],"prior":[57,105],"generation,":[58,82],"which":[59],"is":[60,129],"utilized":[61],"system":[64],"matrix":[65],"solve":[67],"inverse":[69],"problem.":[70],"model":[74],"first":[75],"undergoes":[76],"coarse":[77],"training":[78,88],"ensure":[80],"stable":[81],"followed":[83],"a":[85,97],"dedicated":[86],"fine":[87],"sharpen":[90],"detailed":[91],"fidelity.":[92],"novel":[98],"dual-domain":[99,103,110,115,134],"denoising":[100],"network,":[101,106],"named":[102],"that":[107,172],"introduces":[108],"Cartesian-based":[111],"polar-based":[113],"coordinates":[114],"Transformer":[116],"efficiently":[118],"capture":[119],"multiscale":[120],"latent":[121],"representations.":[122],"addition,":[124],"decoder":[126],"withU-conditional":[127],"cross-attention":[128],"proposed":[130],"fully":[132],"preserve":[133],"long-range":[135],"dependencies.":[136],"SPfusion":[137,173],"achieves":[138],"accurate":[139],"noise":[140],"estimation,":[141],"high-fidelity":[142],"detail":[143],"generation":[144],"of":[145,182],"prior,":[149],"well":[151],"high-quality":[153],"reconstructions":[155],"based":[156],"on":[157,162],"model-driven":[158],"methods.":[159],"Experiments":[160],"conducted":[161],"simulation":[163],"data,":[164],"real-world":[165],"measurements,":[166],"publicly":[168],"available":[169,193],"benchmark":[170],"demonstrate":[171],"outperforms":[174],"supervised/unsupervised":[175],"previous":[177],"diffusion-based":[178],"terms":[181],"reconstruction":[183],"accuracy":[184],"stability.":[186],"project":[188],"further":[190],"information":[191],"are":[192],"online.":[194]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2026-01-14T00:00:00"}
