{"id":"https://openalex.org/W3122899507","doi":"https://doi.org/10.1109/tci.2021.3054249","title":"Weighted Tensor Low-Rankness and Learnable Analysis Sparse Representation Model for Texture Preserving Low-Dose CT Reconstruction","display_name":"Weighted Tensor Low-Rankness and Learnable Analysis Sparse Representation Model for Texture Preserving Low-Dose CT Reconstruction","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3122899507","doi":"https://doi.org/10.1109/tci.2021.3054249","mag":"3122899507"},"language":"en","primary_location":{"id":"doi:10.1109/tci.2021.3054249","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tci.2021.3054249","pdf_url":null,"source":{"id":"https://openalex.org/S4210233665","display_name":"IEEE Transactions on Computational Imaging","issn_l":"2333-9403","issn":["2333-9403","2573-0436"],"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 Computational Imaging","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/A5103179870","display_name":"Yuanke Zhang","orcid":"https://orcid.org/0000-0001-8091-0271"},"institutions":[{"id":"https://openalex.org/I202126657","display_name":"Qufu Normal University","ror":"https://ror.org/03ceheh96","country_code":"CN","type":"education","lineage":["https://openalex.org/I202126657"]},{"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":true,"raw_author_name":"Yuanke Zhang","raw_affiliation_strings":["School of Biomedical Engineering, Southern Medical University, Guangzhou, China","School of Computer Science, Qufu Normal University, Rizhao, China"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Southern Medical University, Guangzhou, China","institution_ids":["https://openalex.org/I58200834"]},{"raw_affiliation_string":"School of Computer Science, Qufu Normal University, Rizhao, China","institution_ids":["https://openalex.org/I202126657"]}]},{"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/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Zeng","raw_affiliation_strings":["College of Automation Science and Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Automation Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024645254","display_name":"Zhaoying Bian","orcid":"https://orcid.org/0000-0002-6433-5067"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]},{"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":"Zhaoying Bian","raw_affiliation_strings":["Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Northeastern University, Shenyang, China","Pazhou Laboratory, Guangzhou, China","School of Biomedical Engineering, Guangdong Provincial Key Laborary of Medical Image Processing, Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Southern Medical University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]},{"raw_affiliation_string":"Pazhou Laboratory, Guangzhou, China","institution_ids":[]},{"raw_affiliation_string":"School of Biomedical Engineering, Guangdong Provincial Key Laborary of Medical Image Processing, Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Southern Medical University, Guangzhou, China","institution_ids":["https://openalex.org/I58200834"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034743810","display_name":"Hongbing Lu","orcid":"https://orcid.org/0000-0003-4181-7239"},"institutions":[{"id":"https://openalex.org/I9916479","display_name":"Air Force Medical University","ror":"https://ror.org/00ms48f15","country_code":"CN","type":"education","lineage":["https://openalex.org/I9916479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongbing Lu","raw_affiliation_strings":["School of Biomedical Engineering, Fourth Military Medical University, Xi\u2019an, China","School of Biomedical Engineering, Fourth Military Medical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Fourth Military Medical University, Xi\u2019an, China","institution_ids":["https://openalex.org/I9916479"]},{"raw_affiliation_string":"School of Biomedical Engineering, Fourth Military Medical University, Xi'an, China","institution_ids":["https://openalex.org/I9916479"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006049117","display_name":"Jianhua Ma","orcid":"https://orcid.org/0000-0003-2958-1710"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]},{"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":["Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Northeastern University, Shenyang, China","Pazhou Laboratory, Guangzhou, China","School of Biomedical Engineering, Guangdong Provincial Key Laborary of Medical Image Processing, Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Southern Medical University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]},{"raw_affiliation_string":"Pazhou Laboratory, Guangzhou, China","institution_ids":[]},{"raw_affiliation_string":"School of Biomedical Engineering, Guangdong Provincial Key Laborary of Medical Image Processing, Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Southern Medical University, Guangzhou, China","institution_ids":["https://openalex.org/I58200834"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5103179870"],"corresponding_institution_ids":["https://openalex.org/I202126657","https://openalex.org/I58200834"],"apc_list":null,"apc_paid":null,"fwci":1.3745,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.79964415,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"7","issue":null,"first_page":"321","last_page":"336"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9998000264167786,"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":0.9998000264167786,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9987000226974487,"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/matrix-norm","display_name":"Matrix norm","score":0.6715599298477173},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.6164215803146362},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5718404054641724},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5699723362922668},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5121831893920898},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48690927028656006},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.42268916964530945},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.41997525095939636},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4187595844268799},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39573174715042114}],"concepts":[{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.6715599298477173},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.6164215803146362},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5718404054641724},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5699723362922668},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5121831893920898},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48690927028656006},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.42268916964530945},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.41997525095939636},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4187595844268799},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39573174715042114},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tci.2021.3054249","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tci.2021.3054249","pdf_url":null,"source":{"id":"https://openalex.org/S4210233665","display_name":"IEEE Transactions on Computational Imaging","issn_l":"2333-9403","issn":["2333-9403","2573-0436"],"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 Computational Imaging","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G5024088075","display_name":null,"funder_award_id":"2020YFA0712200","funder_id":"https://openalex.org/F4320336026","funder_display_name":"National Key Research and Development Program of China Stem Cell and Translational Research"},{"id":"https://openalex.org/G5559181208","display_name":null,"funder_award_id":"61871383","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/G8462863733","display_name":null,"funder_award_id":"2020M672710","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320336026","display_name":"National Key Research and Development Program of China Stem Cell and Translational Research","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W1966364402","https://openalex.org/W1968238516","https://openalex.org/W1992426838","https://openalex.org/W1995758426","https://openalex.org/W2000015923","https://openalex.org/W2024165284","https://openalex.org/W2037511378","https://openalex.org/W2039506751","https://openalex.org/W2042220165","https://openalex.org/W2043571470","https://openalex.org/W2044465660","https://openalex.org/W2044774090","https://openalex.org/W2045737896","https://openalex.org/W2049856752","https://openalex.org/W2054218460","https://openalex.org/W2054393756","https://openalex.org/W2056370875","https://openalex.org/W2056532343","https://openalex.org/W2075157914","https://openalex.org/W2079705627","https://openalex.org/W2080843093","https://openalex.org/W2090457307","https://openalex.org/W2091449379","https://openalex.org/W2094366314","https://openalex.org/W2095631289","https://openalex.org/W2098092211","https://openalex.org/W2103972604","https://openalex.org/W2104050041","https://openalex.org/W2107844156","https://openalex.org/W2119259145","https://openalex.org/W2133665775","https://openalex.org/W2136396015","https://openalex.org/W2144783994","https://openalex.org/W2145962650","https://openalex.org/W2149256982","https://openalex.org/W2149300224","https://openalex.org/W2153663612","https://openalex.org/W2160547390","https://openalex.org/W2164278908","https://openalex.org/W2171697262","https://openalex.org/W2288483235","https://openalex.org/W2505029951","https://openalex.org/W2518642309","https://openalex.org/W2567331605","https://openalex.org/W2578922756","https://openalex.org/W2603901191","https://openalex.org/W2755989196","https://openalex.org/W2903417171","https://openalex.org/W2904393137","https://openalex.org/W2914014776","https://openalex.org/W2952026614","https://openalex.org/W2960143795","https://openalex.org/W2963885538","https://openalex.org/W2963980562","https://openalex.org/W3101963065","https://openalex.org/W4250857377","https://openalex.org/W4292363360","https://openalex.org/W6660475368"],"related_works":["https://openalex.org/W1980381208","https://openalex.org/W2258058088","https://openalex.org/W1826223126","https://openalex.org/W4362519919","https://openalex.org/W2890370013","https://openalex.org/W2753062694","https://openalex.org/W2953204310","https://openalex.org/W2030927653","https://openalex.org/W2062063412","https://openalex.org/W3155724094"],"abstract_inverted_index":{"In":[0,79],"CT":[1,49,66,184],"images,":[2],"tissue":[3],"structures":[4],"and":[5,12,19,38,74,89,102,126,240],"lesion":[6],"changes":[7],"illustrate":[8],"evident":[9],"non-local":[10,35,100],"self-similarity":[11],"regionally":[13],"constant":[14],"properties.":[15],"The":[16,221],"low-rank":[17,124],"model":[18,24,94],"the":[20,32,39,47,61,99,121,128,138,146,163,173,177,189,202,205,215,218,225],"learnable":[21],"sparse":[22],"representation":[23],"are":[25],"powerful":[26],"tools":[27],"that":[28,145,224],"can":[29,149,228],"respectively":[30],"encode":[31,98],"correlations":[33,101],"among":[34],"similar":[36],"patches":[37],"sparsity":[40,105],"in":[41,162,204,235],"a":[42,84,110,154,182,196],"local":[43,103],"transformed":[44,104,152],"subspace":[45],"about":[46],"underlying":[48],"image.":[50],"Existing":[51],"Model-Based":[52],"Iterative":[53],"Reconstruction":[54],"(MBIR)":[55],"methods":[56,234],"generally":[57],"adopt":[58],"one":[59],"of":[60,176,217,237],"two":[62],"models":[63],"alone":[64],"for":[65],"reconstruction,":[67],"which":[68,167],"might":[69],"suffer":[70],"from":[71],"modelling":[72],"deficiency":[73],"hampers":[75],"their":[76],"reconstruction":[77,185],"performance.":[78],"this":[80],"study,":[81],"we":[82,108],"presented":[83,190],"novel":[85,111,183],"Weighted":[86,112,129],"Tensor":[87,113,130],"Low-Rank":[88],"Learnable":[90],"Analysis":[91],"Sparse":[92],"Representation":[93],"(WTLR-LASR)":[95],"to":[96,119,136,153,170,199,213],"simultaneously":[97],"natures.":[106],"Specifically,":[107],"developed":[109],"Nuclear":[114,131],"Norm":[115,132],"Minimization":[116],"(WTNNM)":[117],"formulation":[118],"characterize":[120],"weighted":[122,155],"tensor":[123],"model,":[125],"introduced":[127,195],"Proximal":[133],"(WTNNP)":[134],"operator":[135],"solve":[137],"non-convex":[139],"WTNNM":[140],"problem.":[141,179],"We":[142,180,193],"further":[143],"proved":[144],"WTNNP":[147,178],"problem":[148,161],"be":[150],"equivalently":[151],"matrix":[156],"nuclear":[157],"norm":[158],"proximal":[159],"(WMNNP)":[160],"Fourier":[164],"transform":[165],"domain,":[166],"allowed":[168],"us":[169],"easily":[171],"reach":[172],"closed-form":[174],"optimum":[175],"proposed":[181,206,219,226],"algorithm":[186,198,227],"based":[187],"on":[188],"WTLR-LASR":[191],"model.":[192],"also":[194],"genetic":[197],"automatically":[200],"select":[201],"parameters":[203],"algorithm.":[207,220],"Extensive":[208],"experimental":[209],"studies":[210],"were":[211],"performed":[212],"validate":[214],"effectiveness":[216],"results":[222],"demonstrate":[223],"achieve":[229],"noticeable":[230],"improvements":[231],"over":[232],"state-of-the-art":[233],"terms":[236],"noise":[238],"suppression":[239],"textures":[241],"preservation.":[242]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}