{"id":"https://openalex.org/W2912238674","doi":"https://doi.org/10.1109/cisp-bmei.2018.8633142","title":"A Novel Method of Synthetic CT Generation from MR Images Based on Convolutional Neural Networks","display_name":"A Novel Method of Synthetic CT Generation from MR Images Based on Convolutional Neural Networks","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2912238674","doi":"https://doi.org/10.1109/cisp-bmei.2018.8633142","mag":"2912238674"},"language":"en","primary_location":{"id":"doi:10.1109/cisp-bmei.2018.8633142","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2018.8633142","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","raw_type":"proceedings-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/A5100406322","display_name":"Guang Li","orcid":"https://orcid.org/0000-0003-2898-2504"},"institutions":[{"id":"https://openalex.org/I4210134419","display_name":"Neusoft (China)","ror":"https://ror.org/02zc84r97","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210134419"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guang Li","raw_affiliation_strings":["Precision Image Technique R&D Department, Neusoft Medical System Co., Ltd., Shenyang, China"],"affiliations":[{"raw_affiliation_string":"Precision Image Technique R&D Department, Neusoft Medical System Co., Ltd., Shenyang, China","institution_ids":["https://openalex.org/I4210134419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017499714","display_name":"Lu Bai","orcid":"https://orcid.org/0000-0003-1242-5412"},"institutions":[{"id":"https://openalex.org/I4210134419","display_name":"Neusoft (China)","ror":"https://ror.org/02zc84r97","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210134419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lu Bai","raw_affiliation_strings":["Precision Image Technique R&D Department, Neusoft Medical System Co., Ltd., Shenyang, China"],"affiliations":[{"raw_affiliation_string":"Precision Image Technique R&D Department, Neusoft Medical System Co., Ltd., Shenyang, China","institution_ids":["https://openalex.org/I4210134419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038549206","display_name":"Chuanwei Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210134419","display_name":"Neusoft (China)","ror":"https://ror.org/02zc84r97","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210134419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuanwei Zhu","raw_affiliation_strings":["Precision Image Technique R&D Department, Neusoft Medical System Co., Ltd., Shenyang, China"],"affiliations":[{"raw_affiliation_string":"Precision Image Technique R&D Department, Neusoft Medical System Co., Ltd., Shenyang, China","institution_ids":["https://openalex.org/I4210134419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050397927","display_name":"Enhe Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210134419","display_name":"Neusoft (China)","ror":"https://ror.org/02zc84r97","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210134419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Enhe Wu","raw_affiliation_strings":["Precision Image Technique R&D Department, Neusoft Medical System Co., Ltd., Shenyang, China"],"affiliations":[{"raw_affiliation_string":"Precision Image Technique R&D Department, Neusoft Medical System Co., Ltd., Shenyang, China","institution_ids":["https://openalex.org/I4210134419"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047185505","display_name":"Ruibing Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I4210134419","display_name":"Neusoft (China)","ror":"https://ror.org/02zc84r97","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210134419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruibing Ma","raw_affiliation_strings":["Precision Image Technique R&D Department, Neusoft Medical System Co., Ltd., Shenyang, China"],"affiliations":[{"raw_affiliation_string":"Precision Image Technique R&D Department, Neusoft Medical System Co., Ltd., Shenyang, China","institution_ids":["https://openalex.org/I4210134419"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100406322"],"corresponding_institution_ids":["https://openalex.org/I4210134419"],"apc_list":null,"apc_paid":null,"fwci":1.2377,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.81012486,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9980999827384949,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9948999881744385,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7420967817306519},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7131345868110657},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6834574341773987},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5514078736305237},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5242081880569458},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.49443817138671875},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4874110519886017},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.43904682993888855},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3146670162677765}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7420967817306519},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7131345868110657},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6834574341773987},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5514078736305237},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5242081880569458},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.49443817138671875},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4874110519886017},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.43904682993888855},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3146670162677765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cisp-bmei.2018.8633142","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2018.8633142","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2057743740","https://openalex.org/W2142082007","https://openalex.org/W2208340121","https://openalex.org/W2523213734","https://openalex.org/W2567079332","https://openalex.org/W2745006834","https://openalex.org/W2794022343","https://openalex.org/W2962914239","https://openalex.org/W2963073614"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2397288865","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W2368524271","https://openalex.org/W4247116873","https://openalex.org/W2811106690","https://openalex.org/W2590798552","https://openalex.org/W2964954556","https://openalex.org/W2353456014"],"abstract_inverted_index":{"The":[0],"synthesis":[1,27],"of":[2,127],"medical":[3,20],"images":[4,16,180,187,206],"from":[5,18,84,98],"one":[6],"modality":[7],"to":[8,28,37,101,152,198],"another":[9],"is":[10,49,195],"an":[11],"intensity":[12,123],"transformation":[13],"between":[14,202],"two":[15],"acquired":[17],"different":[19,203],"devices,":[21],"such":[22,56],"as":[23,57],"Magnetic":[24],"Resonance":[25],"(MR)image":[26],"Computed":[29],"Tomography":[30],"(CT)image,":[31],"or":[32,191],"MR":[33,45,85,99,119,163,204],"T1":[34],"weighted":[35,39,43],"(T1W)image":[36],"T2":[38],"(T2W)or":[40],"proton":[41],"density":[42],"(PDW)image.":[44],"based":[46,74],"synthetic":[47,81],"CT":[48,82,102,121,165,179],"very":[50],"useful":[51],"for":[52,61,95,137,185],"some":[53,110],"clinical":[54],"cases,":[55],"PET":[58],"attenuation":[59],"correction":[60],"PET/MR,":[62],"MR/CT":[63],"registration":[64],"etc.":[65],"In":[66],"this":[67],"paper,":[68],"we":[69,143],"propose":[70],"a":[71,89],"novel":[72],"method":[73,175],"on":[75],"fully":[76],"convolutional":[77,138],"networks":[78,140],"(FCN)to":[79],"generate":[80],"image":[83,96,100,122],"image.":[86,103],"We":[87],"adopt":[88,144],"u-net":[90],"like":[91],"structure":[92,159],"FCN":[93],"model":[94],"regression":[97],"To":[104],"achieve":[105],"better":[106],"result,":[107],"there":[108],"are":[109,168],"key":[111],"steps":[112],"proposed.":[113],"Firstly,":[114],"the":[115,132,186],"preprocessing":[116],"step,":[117],"normalize":[118],"and":[120,164,193],"using":[124],"mean":[125],"value":[126],"brain":[128,162],"tissue.":[129],"Secondly,":[130],"Propose":[131],"tissue":[133],"focused":[134],"loss":[135],"function":[136],"neural":[139],"(CNN)regression.":[141],"Thirdly,":[142],"three":[145],"orthogonal":[146],"planner":[147],"convolution":[148,151],"instead":[149],"3D":[150,158],"avoid":[153],"huge":[154],"computation":[155],"however":[156],"keep":[157],"information.":[160],"Fifteen":[161],"data":[166],"pairs":[167],"analyzed.":[169],"Experiment":[170],"results":[171,201],"show":[172],"that":[173],"our":[174],"can":[176],"accurately":[177],"synthesize":[178],"in":[181],"various":[182],"scenarios,":[183],"even":[184],"with":[188],"large":[189],"rotation":[190],"lesion,":[192],"it":[194],"also":[196],"extended":[197],"get":[199],"accurate":[200],"sequence":[205],"synthesis.":[207]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":6},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}