{"id":"https://openalex.org/W4410115968","doi":"https://doi.org/10.1088/1748-0221/20/05/p05004","title":"An improving reconstruction network for sparse-view spectral CT based on dual-domain hybrid encoder integrating ResNet and Transformer","display_name":"An improving reconstruction network for sparse-view spectral CT based on dual-domain hybrid encoder integrating ResNet and Transformer","publication_year":2025,"publication_date":"2025-05-01","ids":{"openalex":"https://openalex.org/W4410115968","doi":"https://doi.org/10.1088/1748-0221/20/05/p05004"},"language":"en","primary_location":{"id":"doi:10.1088/1748-0221/20/05/p05004","doi":"https://doi.org/10.1088/1748-0221/20/05/p05004","is_oa":false,"landing_page_url":"https://doi.org/10.1088/1748-0221/20/05/p05004","pdf_url":null,"source":{"id":"https://openalex.org/S116045149","display_name":"Journal of Instrumentation","issn_l":"1748-0221","issn":["1748-0221"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","dongbi-d","jufo-1","ki-jl-1","norway-1","poland-70","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310311669","host_organization_name":"Institute of Physics","host_organization_lineage":["https://openalex.org/P4310311669"],"host_organization_lineage_names":["Institute of Physics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Instrumentation","raw_type":"journal-article"},"volume":null,"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/A5037289825","display_name":"Fanning Kong","orcid":"https://orcid.org/0000-0002-5554-0181","observed_orcids":["https://orcid.org/0000-0002-5554-0181"]},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fanning Kong","raw_affiliation_strings":["School of Microelectronics, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-5554-0181","affiliations":[{"raw_affiliation_string":"School of Microelectronics, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009572638","display_name":"Zaifeng Shi","orcid":"https://orcid.org/0000-0002-3851-5697","observed_orcids":["https://orcid.org/0000-0002-3851-5697"]},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zaifeng Shi","raw_affiliation_strings":["School of Microelectronics, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin, China","Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology, No. 92 Weijin Road, Nankai District, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-3851-5697","affiliations":[{"raw_affiliation_string":"School of Microelectronics, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology, No. 92 Weijin Road, Nankai District, Tianjin, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Tianhao Ge","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianhao Ge","raw_affiliation_strings":["School of Microelectronics, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Microelectronics, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100640257","display_name":"Qiwei Li","orcid":"https://orcid.org/0009-0003-1469-6504","observed_orcids":["https://orcid.org/0009-0003-1469-6504","https://orcid.org/0000-0002-1020-3050"]},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiwei Li","raw_affiliation_strings":["School of Microelectronics, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Microelectronics, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064304245","display_name":"Qingjie Cao","orcid":"https://orcid.org/0000-0002-7087-2651","observed_orcids":["https://orcid.org/0000-0002-7087-2651"]},"institutions":[{"id":"https://openalex.org/I15062923","display_name":"Tianjin Normal University","ror":"https://ror.org/05x2td559","country_code":"CN","type":"education","lineage":["https://openalex.org/I15062923"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingjie Cao","raw_affiliation_strings":["School of Mathematical Sciences, Tianjin Normal University, No. 393 Binshui West Road, Xiqing District, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, Tianjin Normal University, No. 393 Binshui West Road, Xiqing District, Tianjin, China","institution_ids":["https://openalex.org/I15062923"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":3290,"currency":"USD","value_usd":3290},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05737048,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"20","issue":"05","first_page":"P05004","last_page":"P05004"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9340999722480774,"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"}},"topics":[{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9340999722480774,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.048900000751018524,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.0026000000070780516,"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/sparse-view-ct-reconstruction","display_name":"sparse-view CT reconstruction","score":0.9089999794960022},{"id":"https://openalex.org/keywords/dual-energy-ct","display_name":"dual-energy CT","score":0.8450000286102295},{"id":"https://openalex.org/keywords/spectral-ct","display_name":"spectral CT","score":0.7919999957084656},{"id":"https://openalex.org/keywords/differential-learning","display_name":"differential learning","score":0.8870000243186951},{"id":"https://openalex.org/keywords/breast-ct","display_name":"breast CT","score":0.6069999933242798},{"id":"https://openalex.org/keywords/radiation-dose-reduction","display_name":"radiation dose reduction","score":0.8019999861717224}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6803624033927917},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6655954718589783},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.6452929973602295},{"id":"https://openalex.org/C2944601119","wikidata":"https://www.wikidata.org/wiki/Q43744058","display_name":"Residual neural network","level":3,"score":0.6339353322982788},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6177056431770325},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33911722898483276},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.19979771971702576},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.16044092178344727},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06689739227294922},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.05657437443733215},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1088/1748-0221/20/05/p05004","doi":"https://doi.org/10.1088/1748-0221/20/05/p05004","is_oa":false,"landing_page_url":"https://doi.org/10.1088/1748-0221/20/05/p05004","pdf_url":null,"source":{"id":"https://openalex.org/S116045149","display_name":"Journal of Instrumentation","issn_l":"1748-0221","issn":["1748-0221"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","dongbi-d","jufo-1","ki-jl-1","norway-1","poland-70","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310311669","host_organization_name":"Institute of Physics","host_organization_lineage":["https://openalex.org/P4310311669"],"host_organization_lineage_names":["Institute of Physics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Instrumentation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1580389772","https://openalex.org/W1926920987","https://openalex.org/W1983281817","https://openalex.org/W2096380898","https://openalex.org/W2156767721","https://openalex.org/W2394503167","https://openalex.org/W2574952845","https://openalex.org/W2584483805","https://openalex.org/W2793419304","https://openalex.org/W2796256498","https://openalex.org/W2914583164","https://openalex.org/W2930377639","https://openalex.org/W2964446959","https://openalex.org/W3002768411","https://openalex.org/W3006125542","https://openalex.org/W3098281398","https://openalex.org/W3103878770","https://openalex.org/W3109703258","https://openalex.org/W3121962679","https://openalex.org/W3123241743","https://openalex.org/W3127751679","https://openalex.org/W3157089313","https://openalex.org/W3184365095","https://openalex.org/W3203971980","https://openalex.org/W4210835301","https://openalex.org/W4285489784","https://openalex.org/W4296965639","https://openalex.org/W4308371836","https://openalex.org/W4319998081","https://openalex.org/W4320185942","https://openalex.org/W4327893763","https://openalex.org/W4360939568","https://openalex.org/W4362603432","https://openalex.org/W4366832204","https://openalex.org/W4378214868","https://openalex.org/W4388524608","https://openalex.org/W4390871642","https://openalex.org/W4390872971","https://openalex.org/W4402054824","https://openalex.org/W6683211679","https://openalex.org/W6790275670","https://openalex.org/W6791135319","https://openalex.org/W6843198327","https://openalex.org/W6846345920"],"related_works":["https://openalex.org/W2599472179","https://openalex.org/W4323057981","https://openalex.org/W4390516098","https://openalex.org/W3178607569","https://openalex.org/W2181948922","https://openalex.org/W2384362569","https://openalex.org/W4308408209","https://openalex.org/W4301783946","https://openalex.org/W3196952692","https://openalex.org/W2142795561"],"abstract_inverted_index":{"Abstract":[0],"Sparse-view":[1],"Computed":[2],"Tomography":[3],"(CT)":[4],"is":[5,79],"an":[6,55,90,158],"effective":[7],"method":[8],"for":[9,218],"reducing":[10],"radiation":[11],"dose.":[12],"However,":[13],"the":[14,17,24,36,47,67,72,121,135],"incompleteness":[15],"of":[16,75,81,152,181,187,194],"projection":[18,37,83,122],"results":[19,201],"in":[20,23,34,120,212],"streaking":[21,128],"artifacts":[22,119,129,207],"reconstructed":[25],"images.":[26],"Dual":[27],"energy":[28],"CT":[29,61,167],"Data":[30],"complementarity":[31],"and":[32,38,89,100,118,130,138,145,157,191],"diversity":[33],"both":[35],"image":[39,91,137,168,210],"domains":[40],"represent":[41],"a":[42,82,106,111,148,175,179,185,192],"promising":[43],"solution":[44],"to":[45,65,71,109,164],"recover":[46,66],"missing":[48,68],"information":[49,69],"from":[50],"sparse":[51],"views.":[52],"We":[53],"proposed":[54,172],"end-to-end":[56],"sparse-view":[57,149,213],"dual-domain":[58],"improved":[59],"dual-energy":[60],"reconstruction":[62,169],"network":[63,78],"(DdDe-Net)":[64],"due":[70],"reduced":[73],"number":[74],"projections.":[76],"The":[77,124,199],"comprised":[80],"domain":[84,92],"data":[85,93,156],"correction":[86,94],"module":[87,95,108],"(PDDC-Net)":[88],"(IDDC-Net).":[96],"In":[97],"PDDC-Net,":[98],"ResNet":[99],"Transformer":[101],"architectures":[102],"are":[103],"combined":[104],"with":[105],"residual":[107],"create":[110],"hybrid":[112],"encoder":[113],"structure,":[114],"effectively":[115,205],"suppressing":[116],"noise":[117],"domain.":[123],"IDDC-Net":[125],"further":[126],"reduces":[127],"preserves":[131],"tissue":[132],"details":[133,211],"through":[134],"prior":[136],"differential":[139],"learning":[140],"process.":[141],"DdDe-Net":[142,204],"was":[143],"trained":[144],"validated":[146],"on":[147],"extended":[150],"dataset":[151],"simulated":[153],"breast":[154],"DECT":[155],"abdominal":[159],"slice":[160],"simulation":[161],"dataset.":[162],"Compared":[163],"several":[165],"mainstream":[166],"algorithms,":[170],"our":[171],"algorithm":[173],"demonstrates":[174],"notable":[176],"advantage,":[177],"achieving":[178],"RMSE":[180],"0.0118":[182],"\u00b1":[183,189,196],"0.0032,":[184],"SSIM":[186],"0.9688":[188],"0.0177,":[190],"PSNR":[193],"39.83":[195],"1.14":[197],"dB.":[198],"experimental":[200],"indicate":[202],"that":[203],"mitigates":[206],"while":[208],"preserving":[209],"DECT,":[214],"underscoring":[215],"its":[216],"potential":[217],"practical":[219],"applications.":[220]},"counts_by_year":[],"updated_date":"2026-10-10T09:11:00.788812","created_date":"2025-10-10T00:00:00"}
