{"id":"https://openalex.org/W4321091612","doi":"https://doi.org/10.1142/s1793962324500132","title":"Synthesizing human brain CT images from MRI with deep learning","display_name":"Synthesizing human brain CT images from MRI with deep learning","publication_year":2023,"publication_date":"2023-02-16","ids":{"openalex":"https://openalex.org/W4321091612","doi":"https://doi.org/10.1142/s1793962324500132"},"language":"en","primary_location":{"id":"doi:10.1142/s1793962324500132","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s1793962324500132","pdf_url":null,"source":{"id":"https://openalex.org/S107361000","display_name":"Advances in Complex Systems","issn_l":"0219-5259","issn":["0219-5259","1793-6802","1793-9615","1793-9623"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Modeling, Simulation, and Scientific Computing","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/A5101121205","display_name":"Longfei Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Longfei Zhou","raw_affiliation_strings":["Duke University, Durham, NC 27705, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke University, Durham, NC 27705, USA","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063968957","display_name":"Chenghan Pu","orcid":"https://orcid.org/0000-0003-1825-0393"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenghan Pu","raw_affiliation_strings":["Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 210000, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 210000, P. R. China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089722148","display_name":"Yuyang Lu","orcid":"https://orcid.org/0000-0001-6168-0124"},"institutions":[{"id":"https://openalex.org/I111599522","display_name":"Jiangnan University","ror":"https://ror.org/04mkzax54","country_code":"CN","type":"education","lineage":["https://openalex.org/I111599522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuyang Lu","raw_affiliation_strings":["Jiangnan University, Wuxi, Jiangsu 214000, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jiangnan University, Wuxi, Jiangsu 214000, P. R. China","institution_ids":["https://openalex.org/I111599522"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100386204","display_name":"Ying Zhang","orcid":"https://orcid.org/0000-0003-0509-1098"},"institutions":[{"id":"https://openalex.org/I111599522","display_name":"Jiangnan University","ror":"https://ror.org/04mkzax54","country_code":"CN","type":"education","lineage":["https://openalex.org/I111599522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Zhang","raw_affiliation_strings":["Jiangnan University, Wuxi, Jiangsu 214000, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jiangnan University, Wuxi, Jiangsu 214000, P. R. China","institution_ids":["https://openalex.org/I111599522"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100606583","display_name":"Ke Han","orcid":"https://orcid.org/0000-0002-1390-8152"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Han","raw_affiliation_strings":["Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210000, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210000, P. R. China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089343998","display_name":"Yirui Jin","orcid":null},"institutions":[{"id":"https://openalex.org/I111599522","display_name":"Jiangnan University","ror":"https://ror.org/04mkzax54","country_code":"CN","type":"education","lineage":["https://openalex.org/I111599522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"YiRui Jin","raw_affiliation_strings":["Jiangnan University, Wuxi, Jiangsu 214000, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jiangnan University, Wuxi, Jiangsu 214000, P. R. China","institution_ids":["https://openalex.org/I111599522"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076962436","display_name":"Shengquan Zhang","orcid":"https://orcid.org/0000-0001-6098-1208"},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Shengquan Zhang","raw_affiliation_strings":["The University of Queensland, Brisbane, QLD 4072, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Queensland, Brisbane, QLD 4072, Australia","institution_ids":["https://openalex.org/I165143802"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101532377","display_name":"Kaihua Liu","orcid":"https://orcid.org/0000-0002-8221-0129"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaihua Liu","raw_affiliation_strings":["Harbin Institute of Technology, Weihai, Shandong 264209, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Weihai, Shandong 264209, P. R. China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101121205"],"corresponding_institution_ids":["https://openalex.org/I170897317"],"apc_list":null,"apc_paid":null,"fwci":0.2079,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.53193457,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"15","issue":"01","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9980999827384949,"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"}},"topics":[{"id":"https://openalex.org/T10522","display_name":"Medical Imaging 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"}},{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9965999722480774,"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/T10862","display_name":"AI in cancer detection","score":0.9754999876022339,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7089264392852783},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6816853880882263},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6189828515052795},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.5906835198402405},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5677037239074707},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4536144733428955},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.4418284595012665},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39241164922714233},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.3041054606437683},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2187008261680603}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7089264392852783},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6816853880882263},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6189828515052795},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.5906835198402405},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5677037239074707},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4536144733428955},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4418284595012665},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39241164922714233},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.3041054606437683},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2187008261680603},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s1793962324500132","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s1793962324500132","pdf_url":null,"source":{"id":"https://openalex.org/S107361000","display_name":"Advances in Complex Systems","issn_l":"0219-5259","issn":["0219-5259","1793-6802","1793-9615","1793-9623"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Modeling, Simulation, and Scientific Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W66427752","https://openalex.org/W1591163814","https://openalex.org/W1901129140","https://openalex.org/W1984473052","https://openalex.org/W2016543105","https://openalex.org/W2021177063","https://openalex.org/W2043626403","https://openalex.org/W2044967973","https://openalex.org/W2057743740","https://openalex.org/W2080858163","https://openalex.org/W2083927153","https://openalex.org/W2137013440","https://openalex.org/W2142082007","https://openalex.org/W2162246940","https://openalex.org/W2167157872","https://openalex.org/W2208340121","https://openalex.org/W2346145504","https://openalex.org/W2403686457","https://openalex.org/W2513595145","https://openalex.org/W2523468284","https://openalex.org/W2559655401","https://openalex.org/W2607711656","https://openalex.org/W2807888536","https://openalex.org/W2808185485","https://openalex.org/W2808312419","https://openalex.org/W2884436604","https://openalex.org/W2890139949","https://openalex.org/W2962793481","https://openalex.org/W2963073614","https://openalex.org/W2963176524","https://openalex.org/W2963403405","https://openalex.org/W2963767194","https://openalex.org/W2963890275","https://openalex.org/W2996290406","https://openalex.org/W3090615484","https://openalex.org/W3101123465","https://openalex.org/W3105747145","https://openalex.org/W3131526619","https://openalex.org/W4240805545"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4375867731","https://openalex.org/W3037187668","https://openalex.org/W2611989081","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Rapid":[0],"development":[1],"of":[2,31,92,125,131,179,265,271,278],"artificial":[3],"intelligence":[4],"techniques":[5],"significantly":[6],"promotes":[7],"important":[8],"medical":[9,16],"imaging":[10],"applications":[11],"such":[12,48],"as":[13,49,153],"disease":[14,314],"diagnosis,":[15],"image":[17,297],"analysis":[18],"and":[19,54,73,128,165,176,205,213,225,230,251,273,304],"cross-modality":[20],"synthesis.":[21],"It":[22],"is":[23,143],"valuable":[24],"to":[25,63,77,88,107,145,155,169,188,198,232],"synthesize":[26,108,233],"Computed":[27],"Tomography":[28],"(CT)":[29],"scans":[30,39,167],"human":[32,110,234,294],"brains":[33],"from":[34,114,134,210,238,257,286],"Magnetic":[35],"Resonance":[36],"Imaging":[37,137],"(MRI)":[38],"because":[40],"CT":[41,79,94,112,127,166,175,196,212,236,255,296,300,318],"images":[42,80,95,113,116,130,150,187,197,237,256,301,306],"contain":[43],"particular":[44],"information":[45],"for":[46,309],"diseases":[47],"malignant":[50],"tumors,":[51],"cerebrovascular":[52],"malformations":[53],"aneurysms.":[55],"Although":[56],"there":[57,84],"has":[58],"been":[59],"many":[60],"studies":[61],"trying":[62],"apply":[64],"machine":[65,99,118,156,283],"learning":[66,100,119,157,284],"methods":[67],"(e.g.,":[68],"fully":[69],"convolutional":[70],"neural":[71,218],"networks":[72,219],"generative":[74],"adversarial":[75],"networks)":[76],"predict":[78],"based":[81,316],"on":[82,317],"MRI,":[83],"are":[85,151,223,302,307],"still":[86],"opportunities":[87],"increase":[89],"the":[90,97,148,180],"quality":[91],"synthesized":[93],"using":[96,117],"latest":[98],"algorithms.":[101,158],"In":[102],"this":[103,287],"study,":[104],"we":[105],"aim":[106],"high-credibility":[109],"brain":[111,235,295],"MRI":[115,129,164,177,186,191,200,214,239,258,305],"approaches.":[120],"We":[121],"build":[122],"a":[123,170,189,261,267,274],"dataset":[124],"both":[126],"41":[132],"patients":[133],"The":[135,159,281],"Cancer":[136],"Archive.":[138],"A":[139],"data":[140],"pre-processing":[141],"pipeline":[142,160],"designed":[144],"guarantee":[146],"that":[147,244],"processed":[149],"suitable":[152],"inputs":[154],"includes":[161],"(1)":[162],"pairing":[163],"according":[168],"certain":[171],"time":[172],"interval":[173],"between":[174],"exams":[178],"same":[181],"patient,":[182],"(2)":[183],"registering":[184,194],"all":[185,195],"standard":[190],"template,":[192],"(3)":[193],"paired":[199],"images,":[201],"(4)":[202],"intensity":[203],"normalization":[204],"(5)":[206],"extracting":[207],"2D":[208],"slices":[209],"3D":[211],"volumes.":[215],"Three":[216],"deep":[217],"with":[220],"encoder\u2013decoder":[221],"structure":[222],"selected":[224],"implemented":[226],"including":[227],"U-Net,":[228],"U-Net++":[229,245],"pix2pix":[231,252],"images.":[240,319],"Experimental":[241],"results":[242],"illustrate":[243],"shows":[246],"better":[247],"performance":[248],"than":[249],"U-Net":[250],"in":[253,292],"synthesizing":[254],"by":[259],"achieving":[260],"Mean":[262,268],"Squared":[263],"Error":[264,270],"0.025,":[266],"Absolute":[269],"0.082":[272],"Peak":[275],"Signal-to-Noise":[276],"Ratio":[277],"67.90,":[279],"respectively.":[280],"trained":[282],"models":[285],"work":[288],"can":[289],"be":[290],"applied":[291],"future":[293],"prediction":[298],"where":[299],"absent":[303],"available":[308],"specific":[310],"patients,":[311],"thereby":[312],"supporting":[313],"diagnosis":[315]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}