{"id":"https://openalex.org/W4415048832","doi":"https://doi.org/10.1109/tmi.2025.3620222","title":"Unsupervised High-Order Implicit Neural Representation With Line Attention for Metal Artifact Reduction","display_name":"Unsupervised High-Order Implicit Neural Representation With Line Attention for Metal Artifact Reduction","publication_year":2025,"publication_date":"2025-10-10","ids":{"openalex":"https://openalex.org/W4415048832","doi":"https://doi.org/10.1109/tmi.2025.3620222","pmid":"https://pubmed.ncbi.nlm.nih.gov/41071700"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2025.3620222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2025.3620222","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/A5100332203","display_name":"Hongyu Chen","orcid":"https://orcid.org/0000-0002-5329-8854"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyu Chen","raw_affiliation_strings":["School of Computer Science, China University of Geosciences, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-5329-8854","affiliations":[{"raw_affiliation_string":"School of Computer Science, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050449194","display_name":"Shaoguang Huang","orcid":"https://orcid.org/0000-0001-5439-5018"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaoguang Huang","raw_affiliation_strings":["School of Computer Science, China University of Geosciences, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-5439-5018","affiliations":[{"raw_affiliation_string":"School of Computer Science, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024704138","display_name":"Wei He","orcid":"https://orcid.org/0000-0003-3410-0643"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei He","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0003-3410-0643","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005906594","display_name":"Guangyi Yang","orcid":"https://orcid.org/0000-0002-1580-0188"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangyi Yang","raw_affiliation_strings":["School of Electronic Information, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-1580-0188","affiliations":[{"raw_affiliation_string":"School of Electronic Information, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103139834","display_name":"Hongyan Zhang","orcid":"https://orcid.org/0009-0000-5074-0873"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyan Zhang","raw_affiliation_strings":["School of Computer Science, China University of Geosciences, Wuhan, China"],"raw_orcid":"https://orcid.org/0009-0000-5074-0873","affiliations":[{"raw_affiliation_string":"School of Computer Science, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24274273,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"45","issue":"3","first_page":"1237","last_page":"1250"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10834","display_name":"Welding Techniques and Residual Stresses","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T10834","display_name":"Welding Techniques and Residual Stresses","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T12282","display_name":"Mineral Processing and Grinding","score":0.9801999926567078,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6236000061035156},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5464000105857849},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5407999753952026},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.538100004196167},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.49720001220703125},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4846999943256378},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4643000066280365},{"id":"https://openalex.org/keywords/artifact","display_name":"Artifact (error)","score":0.4641999900341034},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.41690000891685486}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7538999915122986},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7264000177383423},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6236000061035156},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5464000105857849},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5407999753952026},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.538100004196167},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5070000290870667},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.49720001220703125},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4846999943256378},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4643000066280365},{"id":"https://openalex.org/C2779010991","wikidata":"https://www.wikidata.org/wiki/Q2720909","display_name":"Artifact (error)","level":2,"score":0.4641999900341034},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.41690000891685486},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.4000000059604645},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.38040000200271606},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.37529999017715454},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.36320000886917114},{"id":"https://openalex.org/C142748172","wikidata":"https://www.wikidata.org/wiki/Q3240002","display_name":"Scan line","level":4,"score":0.3594000041484833},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.3431999981403351},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.335999995470047},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.33070001006126404},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.3052999973297119},{"id":"https://openalex.org/C184652730","wikidata":"https://www.wikidata.org/wiki/Q2357982","display_name":"Attenuation","level":2,"score":0.2985999882221222},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.29499998688697815},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.2944999933242798},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2881999909877777},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.2867000102996826},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.2791999876499176},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.2574999928474426},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2549999952316284}],"mesh":[{"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":"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":"D008670","descriptor_name":"Metals","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D016477","descriptor_name":"Artifacts","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D019047","descriptor_name":"Phantoms, Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019736","descriptor_name":"Prostheses and Implants","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/tmi.2025.3620222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2025.3620222","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:41071700","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41071700","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/G148304942","display_name":null,"funder_award_id":"T2525018","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3951326549","display_name":null,"funder_award_id":"2025AFB394","funder_id":"https://openalex.org/F4320322186","funder_display_name":"Natural Science Foundation of Hubei Province"},{"id":"https://openalex.org/G5433017291","display_name":null,"funder_award_id":"62501550","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/F4320322186","display_name":"Natural Science Foundation of Hubei Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,142,163],"presence":[1],"of":[2,44,134,159,211],"metallic":[3],"implants":[4],"introduces":[5],"bright":[6],"and":[7,20,65,87,95,108,119,153,156,227,233],"dark":[8],"streaks":[9],"that":[10,237],"appear":[11],"in":[12,71,92],"computed":[13],"tomography":[14],"(CT)":[15],"images,":[16,58],"degrading":[17],"image":[18,69,140],"quality":[19],"interfering":[21],"with":[22,167,201,246],"medical":[23],"diagnosis.":[24],"To":[25,50,181],"reduce":[26],"these":[27,212],"artifacts,":[28],"deep":[29],"learning":[30],"approaches":[31],"have":[32],"been":[33],"applied":[34],"for":[35,48,68,79,137],"metal-corrupted":[36],"restoration,":[37],"which":[38,124],"usually":[39,81],"requires":[40],"a":[41,110,187,205],"large":[42],"amount":[43],"simulated":[45],"degraded-clean":[46],"pairs":[47],"training.":[49],"achieve":[51],"metal":[52],"artifact":[53],"reduction":[54],"(MAR)":[55],"without":[56],"reference":[57],"implicit":[59,221],"neural":[60],"representation":[61],"(INR)":[62],"has":[63],"emerged":[64],"shown":[66],"capabilities":[67],"restoration":[70],"an":[72,103],"unsupervised":[73,105,215],"manner.":[74],"However,":[75],"existing":[76],"INR":[77],"methods":[78],"MAR":[80,106,216,243],"treat":[82],"the":[83,126,149,209,214,220,238],"spatial":[84,127,175],"coordinates":[85,128],"independently":[86],"ignore":[88],"their":[89],"correlation,":[90],"resulting":[91],"detail":[93],"loss":[94],"artifacts":[96],"remaining.":[97],"In":[98],"this":[99],"paper,":[100],"we":[101],"propose":[102],"INR-based":[104],"framework":[107,217],"design":[109],"High-order":[111],"Line":[112],"Attention":[113],"Network":[114],"to":[115,196,224],"capture":[116],"local":[117,184,189],"contextual":[118,185],"geometric":[120],"representations":[121],"from":[122,178],"X-rays,":[123],"maps":[125],"into":[129],"discrete":[130],"linear":[131,168],"attenuation":[132],"coefficients":[133],"imaged":[135],"objects":[136],"artifact-free":[138,229],"CT":[139,230],"reconstruction.":[141],"second-order":[143],"feature":[144],"interaction":[145],"can":[146,170,218],"effectively":[147],"improve":[148],"spectral":[150],"bias":[151],"problems":[152],"fit":[154],"low":[155],"high-frequency":[157],"details":[158],"real":[160,234],"signals":[161],"well.":[162],"proposed":[164,239],"line-attention":[165],"module":[166],"complexity":[169],"establish":[171],"global":[172],"relationships":[173],"among":[174],"point":[176],"tokens":[177],"sampled":[179],"rays.":[180],"provide":[182],"more":[183,202],"information,":[186],"multiple":[188],"adjacent":[190],"ray":[191],"sampling":[192],"strategy":[193],"is":[194],"adopted":[195],"compose":[197],"several":[198],"sub-fan":[199],"beams":[200],"context":[203],"as":[204],"training":[206],"batch.":[207],"With":[208],"help":[210],"components,":[213],"approximate":[219],"continuous":[222],"function":[223],"estimate":[225],"measurements":[226],"generate":[228],"images.":[231],"Simulated":[232],"experiments":[235],"indicated":[236],"approach":[240],"achieved":[241],"superior":[242],"performance":[244],"compared":[245],"other":[247],"state-of-the-art":[248],"methods.":[249]},"counts_by_year":[],"updated_date":"2026-03-05T07:30:30.508283","created_date":"2025-10-11T00:00:00"}