{"id":"https://openalex.org/W3110610984","doi":"https://doi.org/10.1109/access.2020.3039638","title":"Learning Image From Projection: A Full-Automatic Reconstruction (FAR) Net for Computed Tomography","display_name":"Learning Image From Projection: A Full-Automatic Reconstruction (FAR) Net for Computed Tomography","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3110610984","doi":"https://doi.org/10.1109/access.2020.3039638","mag":"3110610984"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3039638","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3039638","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09265267.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09265267.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021050186","display_name":"Genwei Ma","orcid":"https://orcid.org/0000-0001-5503-8602"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Genwei Ma","raw_affiliation_strings":["Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing, China","School of Mathematical Sciences, Capital Normal University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5503-8602","affiliations":[{"raw_affiliation_string":"Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"School of Mathematical Sciences, Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075126167","display_name":"Yining Zhu","orcid":"https://orcid.org/0000-0003-4498-477X"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yining Zhu","raw_affiliation_strings":["Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing, China","School of Mathematical Sciences, Capital Normal University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4498-477X","affiliations":[{"raw_affiliation_string":"Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"School of Mathematical Sciences, Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100545391","display_name":"Xing Zhao","orcid":"https://orcid.org/0000-0003-2394-9852"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing Zhao","raw_affiliation_strings":["Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing, China","School of Mathematical Sciences, Capital Normal University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2394-9852","affiliations":[{"raw_affiliation_string":"Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"School of Mathematical Sciences, Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I96852419"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.034,"has_fulltext":true,"cited_by_count":18,"citation_normalized_percentile":{"value":0.80401723,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":98},"biblio":{"volume":"8","issue":null,"first_page":"219400","last_page":"219414"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":1.0,"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":1.0,"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":0.9998000264167786,"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":0.9991000294685364,"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/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.7393325567245483},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.6740155220031738},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6660251617431641},{"id":"https://openalex.org/keywords/radon-transform","display_name":"Radon transform","score":0.6466875076293945},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5956868529319763},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4898814558982849},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4615483582019806},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4507260322570801},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42024824023246765},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.381928026676178}],"concepts":[{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.7393325567245483},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.6740155220031738},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6660251617431641},{"id":"https://openalex.org/C197231052","wikidata":"https://www.wikidata.org/wiki/Q979829","display_name":"Radon transform","level":2,"score":0.6466875076293945},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5956868529319763},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4898814558982849},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4615483582019806},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4507260322570801},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42024824023246765},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.381928026676178}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3039638","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3039638","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09265267.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:0053f7d167254694a6e8d1c99fded1a7","is_oa":true,"landing_page_url":"https://doaj.org/article/0053f7d167254694a6e8d1c99fded1a7","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 219400-219414 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3039638","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3039638","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09265267.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5099999904632568,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G2325842134","display_name":"\u7269\u50cf\u51e0\u4f55\u5173\u7cfb\u96be\u4ee5\u7cbe\u786e\u6d4b\u91cf\u7684CT\u91cd\u5efa\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61671311","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2431180751","display_name":null,"funder_award_id":"61501310","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4845966026","display_name":"\u57fa\u4e8e\u5149\u8026\u5408\u63a2\u6d4b\u5668\u548c\u5149\u5b50\u8ba1\u6570\u63a2\u6d4b\u5668\u7684\u80fd\u8c31\u663e\u5faeCT\u5173\u952e\u7406\u8bba\u4e0e\u6280\u672f\u7814\u7a76","funder_award_id":"61971293","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6632353718","display_name":null,"funder_award_id":"61827809","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8236076414","display_name":"\u53cc\u80fd\u8c31CT\u8fed\u4ee3\u91cd\u5efa\u7b97\u6cd5\u7814\u7a76","funder_award_id":"61371195","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320310931","display_name":"Capital Normal University","ror":"https://ror.org/005edt527"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324098","display_name":"Taiyuan University of Technology","ror":"https://ror.org/03kv08d37"},{"id":"https://openalex.org/F4320325599","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3110610984.pdf","grobid_xml":"https://content.openalex.org/works/W3110610984.grobid-xml"},"referenced_works_count":61,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1902027874","https://openalex.org/W1964131702","https://openalex.org/W1972150100","https://openalex.org/W1990919278","https://openalex.org/W2015587558","https://openalex.org/W2035199208","https://openalex.org/W2049633694","https://openalex.org/W2072652205","https://openalex.org/W2094366314","https://openalex.org/W2118718620","https://openalex.org/W2135029798","https://openalex.org/W2142058898","https://openalex.org/W2146583368","https://openalex.org/W2194775991","https://openalex.org/W2203535936","https://openalex.org/W2282734976","https://openalex.org/W2296616510","https://openalex.org/W2520016695","https://openalex.org/W2520302833","https://openalex.org/W2542870090","https://openalex.org/W2544373769","https://openalex.org/W2570202822","https://openalex.org/W2584483805","https://openalex.org/W2610206647","https://openalex.org/W2611467245","https://openalex.org/W2613155248","https://openalex.org/W2743780012","https://openalex.org/W2753044865","https://openalex.org/W2754357950","https://openalex.org/W2760169020","https://openalex.org/W2765650194","https://openalex.org/W2789165139","https://openalex.org/W2793419304","https://openalex.org/W2795714267","https://openalex.org/W2798138518","https://openalex.org/W2803086176","https://openalex.org/W2883633804","https://openalex.org/W2936895602","https://openalex.org/W2947117330","https://openalex.org/W2955646516","https://openalex.org/W2962947361","https://openalex.org/W2963385325","https://openalex.org/W2963392702","https://openalex.org/W2963444790","https://openalex.org/W2964343197","https://openalex.org/W3101114211","https://openalex.org/W3103431207","https://openalex.org/W3103454039","https://openalex.org/W3104324122","https://openalex.org/W3143596294","https://openalex.org/W4240518936","https://openalex.org/W4250955649","https://openalex.org/W6639824700","https://openalex.org/W6677759377","https://openalex.org/W6680012447","https://openalex.org/W6687764522","https://openalex.org/W6734074887","https://openalex.org/W6742825008","https://openalex.org/W6750436725","https://openalex.org/W6948148018"],"related_works":["https://openalex.org/W4231936369","https://openalex.org/W967573802","https://openalex.org/W3089715742","https://openalex.org/W2466075600","https://openalex.org/W4366975566","https://openalex.org/W4301707735","https://openalex.org/W3103782609","https://openalex.org/W2811038336","https://openalex.org/W2079352884","https://openalex.org/W2004988775"],"abstract_inverted_index":{"The":[0,14,101,206],"x-ray":[1],"computed":[2],"tomography":[3],"(CT)":[4],"is":[5,18,44,65,87,95,108,140,148,193,219,249],"essential":[6],"for":[7,67,104,136,146,244],"medical":[8],"diagnosis":[9],"and":[10,38,56,216,253],"industrial":[11],"nondestructive":[12],"testing.":[13],"aim":[15],"of":[16,112,133,164,208],"CT":[17,68,114,122,224],"to":[19,51,170,195,221,233],"recover":[20],"or":[21,46],"reconstruct":[22,196,222],"image":[23,32,94,123,138,225],"from":[24,35,98,226],"projection":[25,99,214,227,247],"data.":[26,100],"However,":[27],"in":[28,79,116,251],"particular,":[29],"the":[30,42,76,83,93,109,113,125,137,172,179,191,199,213,217,223,242,245],"reconstructed":[31],"usually":[33],"suffers":[34],"complex":[36],"artifacts":[37],"noise,":[39],"such":[40,54,105,188,236],"as":[41,237],"sampling":[43],"insufficient":[45],"low-dose":[47],"CT.":[48],"In":[49,157],"order":[50],"deal":[52],"with":[53,75,124,198,229],"issues":[55],"achieve":[57],"reconstruction,":[58,82],"a":[59,106,121,130,162,230],"full":[60],"automatic":[61],"reconstruction":[62,69,115,139],"(FAR)":[63],"net":[64],"proposed":[66,84],"via":[70],"deep":[71,80],"learning":[72,81],"technique.":[73],"Different":[74],"usual":[77],"network":[78,86,90],"neural":[85],"an":[88,189],"end-to-end":[89],"by":[91,150],"which":[92,147],"predicted":[96],"directly":[97],"main":[102],"challenge":[103],"FAR-net":[107,192,218],"space":[110,135],"complexity":[111],"full-connected":[117],"(FC)":[118],"network.":[119],"For":[120],"size":[126,200],"N":[127],"\u00d7":[128],"N,":[129],"typical":[131],"requirement":[132],"memory":[134],"O(N":[141],"<sup":[142],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[143],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">4</sup>":[144],"),":[145],"unacceptable":[149],"conventional":[151,234],"calculation":[152],"device,":[153],"e.g.":[154],"GPU":[155],"workstation.":[156,205],"this":[158],"paper,":[159],"we":[160],"utilize":[161],"series":[163],"smaller":[165],"fully":[166],"connected":[167],"layers":[168],"(FCL)":[169],"replace":[171],"huge":[173],"Radon":[174],"transform":[175],"matrix":[176,182,215,248],"based":[177,239],"on":[178,202],"sparse":[180],"nonnegative":[181],"factorization":[183,243],"(SNMF)":[184],"theory.":[185],"By":[186],"applying":[187],"approach,":[190],"able":[194,220],"images":[197],"512\u00d7512":[201],"only":[203],"single":[204],"results":[207],"numerical":[209],"experiments":[210],"show":[211],"that":[212],"data":[228],"superior":[231],"quality":[232],"methods":[235],"optimization":[238],"approach.":[240],"Meanwhile,":[241],"inverse":[246],"validated":[250],"simulation":[252],"real":[254],"experiments.":[255]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
