{"id":"https://openalex.org/W2789467431","doi":"https://doi.org/10.1117/12.2293244","title":"Sinogram synthesis using convolutional-neural-network for sparsely view-sampled CT","display_name":"Sinogram synthesis using convolutional-neural-network for sparsely view-sampled CT","publication_year":2018,"publication_date":"2018-03-02","ids":{"openalex":"https://openalex.org/W2789467431","doi":"https://doi.org/10.1117/12.2293244","mag":"2789467431"},"language":"en","primary_location":{"id":"doi:10.1117/12.2293244","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2293244","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2018: Image Processing","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/A5040581340","display_name":"Hoyeon Lee","orcid":"https://orcid.org/0000-0002-1165-1509"},"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"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hoyeon Lee","raw_affiliation_strings":["Korea Advanced Institute of Science and Technology (Korea, Republic of)"],"affiliations":[{"raw_affiliation_string":"Korea Advanced Institute of Science and Technology (Korea, Republic of)","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050087440","display_name":"Seungryong Cho","orcid":"https://orcid.org/0000-0002-9409-3628"},"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"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seungryong Cho","raw_affiliation_strings":["Korea Advanced Institute of Science and Technology (Korea, Republic of)"],"affiliations":[{"raw_affiliation_string":"Korea Advanced Institute of Science and Technology (Korea, Republic of)","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100724655","display_name":"Jongha Lee","orcid":"https://orcid.org/0000-0002-1568-6733"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]},{"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"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jongha Lee","raw_affiliation_strings":["Korea Advanced Institute of Science and Technology (Korea, Republic of)","Samsung Electronics (Korea, Republic of)"],"affiliations":[{"raw_affiliation_string":"Korea Advanced Institute of Science and Technology (Korea, Republic of)","institution_ids":["https://openalex.org/I157485424"]},{"raw_affiliation_string":"Samsung Electronics (Korea, Republic of)","institution_ids":["https://openalex.org/I2250650973"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5040581340"],"corresponding_institution_ids":["https://openalex.org/I157485424"],"apc_list":null,"apc_paid":null,"fwci":0.3536,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.61382185,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"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":0.9976999759674072,"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":0.9976999759674072,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9898999929428101,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7796185612678528},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7121297121047974},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5929778218269348},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38150981068611145},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3549264073371887}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7796185612678528},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7121297121047974},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5929778218269348},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38150981068611145},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3549264073371887}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1117/12.2293244","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2293244","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2018: Image Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:hub.hku.hk:10722/345806","is_oa":false,"landing_page_url":"https://hub.hku.hk/handle/10722/345806","pdf_url":null,"source":{"id":"https://openalex.org/S4377196271","display_name":"The HKU Scholars Hub (University of Hong Kong)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I889458895","host_organization_name":"University of Hong Kong","host_organization_lineage":["https://openalex.org/I889458895"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference_Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1518883343","https://openalex.org/W1538131130","https://openalex.org/W1632571000","https://openalex.org/W1885185971","https://openalex.org/W1955857676","https://openalex.org/W1972150100","https://openalex.org/W2002022050","https://openalex.org/W2083927153","https://openalex.org/W2102353889","https://openalex.org/W2133665775","https://openalex.org/W2155346040","https://openalex.org/W2242218935","https://openalex.org/W2593226005","https://openalex.org/W2950094539","https://openalex.org/W6631093291","https://openalex.org/W6632100814","https://openalex.org/W6636549106","https://openalex.org/W6641017118","https://openalex.org/W6690498163","https://openalex.org/W6734902116","https://openalex.org/W6764076272"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Reducing":[0],"the":[1,38,53,67,76,92,113,130,134,138,143,146,150,181,187,193,197,201,214,231],"number":[2],"of":[3,37,78,112,132,145,152,183,227],"projections":[4],"in":[5,16,52,75,129,149,186],"computed":[6],"tomography":[7],"(CT)":[8],"has":[9],"been":[10,61,83],"exploited":[11],"as":[12],"a":[13,99,105],"low-dose":[14],"option":[15],"conjunction":[17],"with":[18],"advanced":[19],"iterative":[20,26],"image":[21,27,80,202,229],"reconstruction":[22,28],"algorithms.":[23],"While":[24],"such":[25],"methods":[29],"do":[30],"provide":[31],"useful":[32],"images":[33],"and":[34,86,179,204,221],"valuable":[35],"insights":[36],"inverse":[39],"imaging":[40],"problems,":[41],"it":[42],"is":[43],"an":[44],"intriguing":[45],"issue":[46],"whether":[47],"missing":[48,68,135],"view":[49,157],"projection":[50],"data":[51],"sinogram":[54,69,100,126,136,148,172,220],"can":[55],"be":[56],"successfully":[57],"recovered.":[58],"There":[59],"have":[60,82,96],"reported":[62],"several":[63],"approaches":[64],"to":[65,191,224],"interpolating":[66],"data.":[70],"Deep-learning":[71],"based":[72,171],"super-resolution":[73,93],"techniques":[74],"field":[77,185],"natural":[79],"enhancement":[81],"recently":[84],"introduced":[85],"showed":[87],"promising":[88],"results.":[89],"Inspired":[90],"by":[91,137,175],"techniques,":[94],"we":[95,165,211],"earlier":[97],"proposed":[98,119],"inpainting":[101],"method":[102,120,174],"that":[103,213],"uses":[104],"convolutional-neural-network":[106],"for":[107],"sparsely":[108],"viewsampled":[109],"CT.":[110],"Despite":[111],"encouraging":[114],"initial":[115],"results,":[116],"our":[117,167],"previously":[118,168],"had":[121],"two":[122],"drawbacks.":[123],"The":[124],"measured":[125],"was":[127,159],"contaminated":[128],"process":[131],"filling":[133],"deep":[139,188],"learning":[140,189],"network.":[141],"Additionally,":[142],"sum":[144],"interpolated":[147],"direction":[151],"detector":[153],"row":[154],"at":[155],"each":[156],"angle":[158],"not":[160],"preserved.":[161],"In":[162],"this":[163],"study,":[164],"improve":[166],"developed":[169],"deep-learning":[170],"synthesis":[173],"adding":[176],"new":[177,215],"layers":[178],"modifying":[180],"size":[182],"receptive":[184],"network":[190],"overcome":[192],"above":[194],"limitations.":[195],"From":[196],"quantitative":[198],"evaluations":[199],"on":[200],"accuracy":[203],"quality":[205,226],"using":[206],"real":[207],"patients\u2019":[208],"CT":[209,228],"images,":[210],"show":[212],"approach":[216],"synthesizes":[217],"more":[218],"accurate":[219],"thus":[222],"leads":[223],"higher":[225],"than":[230],"previous":[232],"one.":[233]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}