{"id":"https://openalex.org/W4401750649","doi":"https://doi.org/10.1109/isbi56570.2024.10635455","title":"Dynamic Representation Learning with Spatial-Frequency Features for Motion Compensated 4D Cone-Beam Reconstruction","display_name":"Dynamic Representation Learning with Spatial-Frequency Features for Motion Compensated 4D Cone-Beam Reconstruction","publication_year":2024,"publication_date":"2024-05-27","ids":{"openalex":"https://openalex.org/W4401750649","doi":"https://doi.org/10.1109/isbi56570.2024.10635455"},"language":"en","primary_location":{"id":"doi:10.1109/isbi56570.2024.10635455","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/isbi56570.2024.10635455","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Symposium on Biomedical Imaging (ISBI)","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/A5024554185","display_name":"Nuo Tong","orcid":"https://orcid.org/0000-0002-0554-5136"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Nuo Tong","raw_affiliation_strings":["Xidian University,AI-Based Big Medical Imaging Data Frontier Research Center, Academy of Advanced Interdisciplinary Research,Shaanxi,China,710071"],"affiliations":[{"raw_affiliation_string":"Xidian University,AI-Based Big Medical Imaging Data Frontier Research Center, Academy of Advanced Interdisciplinary Research,Shaanxi,China,710071","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102967230","display_name":"He Gong","orcid":"https://orcid.org/0000-0001-7843-3154"},"institutions":[{"id":"https://openalex.org/I88830068","display_name":"Shaanxi Normal University","ror":"https://ror.org/0170z8493","country_code":"CN","type":"education","lineage":["https://openalex.org/I88830068"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"He Gong","raw_affiliation_strings":["Shaanxi Normal University,School of Physics and Information Technology,Shaanxi,China,710061"],"affiliations":[{"raw_affiliation_string":"Shaanxi Normal University,School of Physics and Information Technology,Shaanxi,China,710061","institution_ids":["https://openalex.org/I88830068"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017247607","display_name":"Shuiping Gou","orcid":"https://orcid.org/0000-0002-2619-6481"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuiping Gou","raw_affiliation_strings":["Xidian University,AI-Based Big Medical Imaging Data Frontier Research Center, Academy of Advanced Interdisciplinary Research,Shaanxi,China,710071"],"affiliations":[{"raw_affiliation_string":"Xidian University,AI-Based Big Medical Imaging Data Frontier Research Center, Academy of Advanced Interdisciplinary Research,Shaanxi,China,710071","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040115868","display_name":"Wenwei Shi","orcid":"https://orcid.org/0000-0003-2173-2043"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenwei Shi","raw_affiliation_strings":["Xidian University,School of Artificial Intelligence,Shaanxi,China,710071"],"affiliations":[{"raw_affiliation_string":"Xidian University,School of Artificial Intelligence,Shaanxi,China,710071","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Tianhuan Li","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianhuan Li","raw_affiliation_strings":["Xidian University,School of Artificial Intelligence,Shaanxi,China,710071"],"affiliations":[{"raw_affiliation_string":"Xidian University,School of Artificial Intelligence,Shaanxi,China,710071","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100757765","display_name":"Jisheng Li","orcid":"https://orcid.org/0000-0001-9107-1282"},"institutions":[{"id":"https://openalex.org/I88830068","display_name":"Shaanxi Normal University","ror":"https://ror.org/0170z8493","country_code":"CN","type":"education","lineage":["https://openalex.org/I88830068"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jisheng Li","raw_affiliation_strings":["Shaanxi Normal University,School of Physics and Information Technology,Shaanxi,China,710061"],"affiliations":[{"raw_affiliation_string":"Shaanxi Normal University,School of Physics and Information Technology,Shaanxi,China,710061","institution_ids":["https://openalex.org/I88830068"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5024554185"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2249035,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"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":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T10522","display_name":"Medical Imaging 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"}},{"id":"https://openalex.org/T10638","display_name":"Optical measurement and interference techniques","score":0.9958000183105469,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9940000176429749,"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/representation","display_name":"Representation (politics)","score":0.6377200484275818},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6257599592208862},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5902857184410095},{"id":"https://openalex.org/keywords/beam","display_name":"Beam (structure)","score":0.5223663449287415},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5074777007102966},{"id":"https://openalex.org/keywords/cone","display_name":"Cone (formal languages)","score":0.47607630491256714},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4669659435749054},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.30446967482566833},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.28498607873916626},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1601462960243225}],"concepts":[{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6377200484275818},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6257599592208862},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5902857184410095},{"id":"https://openalex.org/C168834538","wikidata":"https://www.wikidata.org/wiki/Q3705329","display_name":"Beam (structure)","level":2,"score":0.5223663449287415},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5074777007102966},{"id":"https://openalex.org/C30014739","wikidata":"https://www.wikidata.org/wiki/Q5159445","display_name":"Cone (formal languages)","level":2,"score":0.47607630491256714},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4669659435749054},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.30446967482566833},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.28498607873916626},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1601462960243225},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi56570.2024.10635455","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/isbi56570.2024.10635455","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326174","display_name":"Shaanxi Province Postdoctoral Science Foundation","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2112095335","https://openalex.org/W2157812230","https://openalex.org/W2194775991","https://openalex.org/W2791871435","https://openalex.org/W2917129907","https://openalex.org/W2936895602","https://openalex.org/W2953467155","https://openalex.org/W3035294798","https://openalex.org/W3105751747","https://openalex.org/W3160008312","https://openalex.org/W3176466780","https://openalex.org/W4312473028"],"related_works":["https://openalex.org/W2371409811","https://openalex.org/W2956921597","https://openalex.org/W4394660771","https://openalex.org/W2070412032","https://openalex.org/W2062195135","https://openalex.org/W2888047994","https://openalex.org/W4223479902","https://openalex.org/W2383812375","https://openalex.org/W2043823063","https://openalex.org/W4299852727"],"abstract_inverted_index":{"Four-dimensional":[0],"cone-beam":[1],"computed":[2],"tomography":[3],"(4D":[4],"CBCT)":[5],"is":[6,37,75,111,146],"a":[7,33,67,83,89],"promising":[8,194],"tool":[9],"to":[10,113,129,148,176],"overcome":[11],"the":[12,19,29,41,44,51,61,95,100,116,131,138,150,158,167,178,181,186,189],"respiratory":[13,46,154],"induced":[14],"organ":[15,63,204],"motion":[16,64,91,143,160,205],"and":[17,48,58,88,118,156,169,203],"alleviate":[18],"serious":[20,55],"negative":[21],"effects":[22],"on":[23,137],"radiation":[24],"therapy":[25],"treatment":[26],"efficiency.":[27],"However,":[28],"projections":[30,103],"collected":[31],"from":[32],"single":[34],"CBCT":[35,163,172],"scan":[36],"extremely":[38],"sparse":[39],"for":[40],"reconstruction":[42,52,191],"of":[43,60,82,166,180],"ten":[45],"phases,":[47],"result":[49],"in":[50,77,196],"results":[53,195],"with":[54,72,185],"streak":[56,96,197],"artifacts":[57,97],"lacking":[59],"vital":[62],"information.":[65],"Thus,":[66],"dynamic":[68],"representation":[69,85,92,108,144],"learning":[70],"framework":[71],"spatial-frequency":[73,84,90,107,142],"features":[74,120],"proposed":[76,147,182,190],"this":[78],"study,":[79],"which":[80],"consists":[81],"enhancement":[86,109],"network":[87,110,145],"network.":[93],"Towards":[94],"caused":[98],"by":[99,126],"sparsely":[101],"sampled":[102],"within":[104],"each":[105],"phase,":[106],"presented":[112],"capture":[114],"both":[115],"global":[117],"local":[119],"as":[121,123,134],"well":[122],"their":[124],"relations":[125],"spatial-Fourier":[127],"blocks":[128],"restore":[130],"anatomical":[132,200],"details":[133],"possible.":[135],"Based":[136],"enhanced":[139],"phase-correlated":[140],"images,":[141],"obtain":[149],"DVFs":[151],"among":[152],"various":[153],"phases":[155],"achieve":[157],"precise":[159],"compensated":[161],"4D":[162,171],"reconstruction.":[164],"Both":[165],"simulated":[168],"clinical":[170],"datasets":[173],"were":[174],"performed":[175],"evaluate":[177],"performance":[179],"framework.":[183],"Compared":[184],"existing":[187],"methods,":[188],"method":[192],"achieves":[193],"artifact":[198],"reduction,":[199],"detail":[201],"restoration,":[202],"representation.":[206]},"counts_by_year":[],"updated_date":"2026-03-25T23:56:10.502304","created_date":"2025-10-10T00:00:00"}
