{"id":"https://openalex.org/W2963392702","doi":"https://doi.org/10.1109/tmi.2018.2823768","title":"Framing U-Net via Deep Convolutional Framelets: Application to Sparse-View CT","display_name":"Framing U-Net via Deep Convolutional Framelets: Application to Sparse-View CT","publication_year":2018,"publication_date":"2018-04-06","ids":{"openalex":"https://openalex.org/W2963392702","doi":"https://doi.org/10.1109/tmi.2018.2823768","mag":"2963392702","pmid":"https://pubmed.ncbi.nlm.nih.gov/29870370"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2018.2823768","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2018.2823768","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/A5027171928","display_name":"Yoseob Han","orcid":"https://orcid.org/0000-0002-0382-7826"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]},{"id":"https://openalex.org/I4210101891","display_name":"Korea Institute of Brain Science","ror":"https://ror.org/017stnw60","country_code":"KR","type":"facility","lineage":["https://openalex.org/I4210101891"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yoseob Han","raw_affiliation_strings":["Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424","https://openalex.org/I4210101891"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012644755","display_name":"Jong Chul Ye","orcid":"https://orcid.org/0000-0001-9763-9609"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]},{"id":"https://openalex.org/I4210101891","display_name":"Korea Institute of Brain Science","ror":"https://ror.org/017stnw60","country_code":"KR","type":"facility","lineage":["https://openalex.org/I4210101891"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jong Chul Ye","raw_affiliation_strings":["Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-9763-9609","affiliations":[{"raw_affiliation_string":"Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424","https://openalex.org/I4210101891"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":44.1989,"has_fulltext":false,"cited_by_count":603,"citation_normalized_percentile":{"value":0.99904808,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"37","issue":"6","first_page":"1418","last_page":"1429"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9991999864578247,"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/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9980999827384949,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6695412397384644},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6469051837921143},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.6367727518081665},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6115888357162476},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5970185995101929},{"id":"https://openalex.org/keywords/framing","display_name":"Framing (construction)","score":0.5007822513580322},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.47723984718322754},{"id":"https://openalex.org/keywords/net","display_name":"Net (polyhedron)","score":0.47591620683670044},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4407188892364502},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34352922439575195},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33965134620666504},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2109287679195404},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10856366157531738},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08094033598899841}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6695412397384644},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6469051837921143},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.6367727518081665},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6115888357162476},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5970185995101929},{"id":"https://openalex.org/C169087156","wikidata":"https://www.wikidata.org/wiki/Q2131593","display_name":"Framing (construction)","level":2,"score":0.5007822513580322},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.47723984718322754},{"id":"https://openalex.org/C14166107","wikidata":"https://www.wikidata.org/wiki/Q253829","display_name":"Net (polyhedron)","level":2,"score":0.47591620683670044},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4407188892364502},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34352922439575195},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33965134620666504},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2109287679195404},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10856366157531738},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08094033598899841},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep 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":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"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":"D006801","descriptor_name":"Humans","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":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/tmi.2018.2823768","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2018.2823768","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:29870370","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/29870370","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":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3047419089","display_name":null,"funder_award_id":"NRF-2016R1A2B3008104","funder_id":"https://openalex.org/F4320322348","funder_display_name":"Korea Science and Engineering Foundation"},{"id":"https://openalex.org/G4456445263","display_name":null,"funder_award_id":"10072064","funder_id":"https://openalex.org/F4320321681","funder_display_name":"Ministry of Trade, Industry and Energy"}],"funders":[{"id":"https://openalex.org/F4320309691","display_name":"American Association of Physicists in Medicine","ror":"https://ror.org/015jknj09"},{"id":"https://openalex.org/F4320321681","display_name":"Ministry of Trade, Industry and Energy","ror":"https://ror.org/008nkqk13"},{"id":"https://openalex.org/F4320322348","display_name":"Korea Science and Engineering Foundation","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320337363","display_name":"National Institute of Biomedical Imaging and Bioengineering","ror":"https://ror.org/00372qc85"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1562968274","https://openalex.org/W1836465849","https://openalex.org/W1901129140","https://openalex.org/W1915360731","https://openalex.org/W1963882359","https://openalex.org/W1968238516","https://openalex.org/W1972150100","https://openalex.org/W1980003430","https://openalex.org/W2037067321","https://openalex.org/W2042430763","https://openalex.org/W2050507755","https://openalex.org/W2058808032","https://openalex.org/W2071847032","https://openalex.org/W2096309518","https://openalex.org/W2133665775","https://openalex.org/W2146337213","https://openalex.org/W2163605009","https://openalex.org/W2196426102","https://openalex.org/W2226146394","https://openalex.org/W2242218935","https://openalex.org/W2280386000","https://openalex.org/W2330127310","https://openalex.org/W2476548250","https://openalex.org/W2485159658","https://openalex.org/W2489519930","https://openalex.org/W2508457857","https://openalex.org/W2515506870","https://openalex.org/W2520016695","https://openalex.org/W2525884435","https://openalex.org/W2542870090","https://openalex.org/W2556016755","https://openalex.org/W2570202822","https://openalex.org/W2574952845","https://openalex.org/W2592048188","https://openalex.org/W2592978821","https://openalex.org/W2617128058","https://openalex.org/W2738743584","https://openalex.org/W2743780012","https://openalex.org/W2761343114","https://openalex.org/W2767579567","https://openalex.org/W2777802649","https://openalex.org/W2795777276","https://openalex.org/W2962903101","https://openalex.org/W2963500592","https://openalex.org/W3103586216","https://openalex.org/W4250955649","https://openalex.org/W6639824700","https://openalex.org/W6681686951","https://openalex.org/W6684191040","https://openalex.org/W6702160259"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2912321008","https://openalex.org/W1496503799","https://openalex.org/W4323832858","https://openalex.org/W2185686261","https://openalex.org/W2324368075","https://openalex.org/W1998607122","https://openalex.org/W2972032537","https://openalex.org/W2079138064","https://openalex.org/W2004988775"],"abstract_inverted_index":{"X-ray":[0],"computed":[1],"tomography":[2],"(CT)":[3],"using":[4,28,42],"sparse":[5],"projection":[6,22,32],"views":[7],"is":[8,62],"a":[9],"recent":[10,68],"approach":[11,27],"to":[12,19,82],"reduce":[13],"the":[14,20,29,67,74,84,100,113,142],"radiation":[15],"dose.":[16],"However,":[17,59],"due":[18],"insufficient":[21],"views,":[23],"an":[24],"analytic":[25],"reconstruction":[26,148],"filtered":[30],"back":[31],"(FBP)":[33],"produces":[34],"severe":[35],"streaking":[36],"artifacts.":[37],"Recently,":[38],"deep":[39,71,92],"learning":[40,93],"approaches":[41],"large":[43],"receptive":[44],"field":[45],"neural":[46],"networks":[47],"such":[48,104],"as":[49,105],"U-Net":[50,87,102],"have":[51],"demonstrated":[52],"impressive":[53],"performance":[54],"for":[55,121],"sparse-view":[56,129],"CT":[57],"reconstruction.":[58],"theoretical":[60],"justification":[61],"still":[63],"lacking.":[64],"Inspired":[65],"by":[66],"theory":[69],"of":[70,77,86,124],"convolutional":[72],"framelets,":[73],"main":[75],"goal":[76],"this":[78],"paper":[79],"is,":[80],"therefore,":[81],"reveal":[83],"limitation":[85],"and":[88,108],"propose":[89],"new":[90,143],"multi-resolution":[91],"schemes.":[94],"In":[95],"particular,":[96],"we":[97,139],"show":[98],"that":[99,141],"alternative":[101],"variants":[103],"dual":[106],"frame":[107,110,115],"tight":[109],"U-Nets":[111],"satisfy":[112],"so-called":[114],"condition":[116],"which":[117],"makes":[118],"them":[119],"better":[120,147],"effective":[122],"recovery":[123],"high":[125],"frequency":[126],"edges":[127],"in":[128],"CT.":[130],"Using":[131],"extensive":[132],"experiments":[133],"with":[134],"real":[135],"patient":[136],"data":[137],"set,":[138],"demonstrate":[140],"network":[144],"architectures":[145],"provide":[146],"performance.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":23},{"year":2025,"cited_by_count":59},{"year":2024,"cited_by_count":66},{"year":2023,"cited_by_count":84},{"year":2022,"cited_by_count":98},{"year":2021,"cited_by_count":87},{"year":2020,"cited_by_count":100},{"year":2019,"cited_by_count":69},{"year":2018,"cited_by_count":16},{"year":2017,"cited_by_count":1}],"updated_date":"2026-08-22T07:34:49.880490","created_date":"2025-10-10T00:00:00"}
