{"id":"https://openalex.org/W3132124887","doi":"https://doi.org/10.1117/12.2580971","title":"4D cone-beam CT deformable registration using unsupervised spatial transformation network","display_name":"4D cone-beam CT deformable registration using unsupervised spatial transformation network","publication_year":2021,"publication_date":"2021-02-12","ids":{"openalex":"https://openalex.org/W3132124887","doi":"https://doi.org/10.1117/12.2580971","mag":"3132124887"},"language":"en","primary_location":{"id":"doi:10.1117/12.2580971","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2580971","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging","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/A5049656223","display_name":"Tonghe Wang","orcid":"https://orcid.org/0000-0001-9021-1204"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tonghe Wang","raw_affiliation_strings":["The Winship Cancer Institute of Emory Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"The Winship Cancer Institute of Emory Univ. (United States)","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011903902","display_name":"Yang Lei","orcid":"https://orcid.org/0000-0002-3572-0345"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yang Lei","raw_affiliation_strings":["The Winship Cancer Institute of Emory Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"The Winship Cancer Institute of Emory Univ. (United States)","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101311536","display_name":"Zhen Tian","orcid":"https://orcid.org/0009-0009-2962-6334"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhen Tian","raw_affiliation_strings":["The Winship Cancer Institute of Emory Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"The Winship Cancer Institute of Emory Univ. (United States)","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021253230","display_name":"Matt Giles","orcid":null},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matt Giles","raw_affiliation_strings":["The Winship Cancer Institute of Emory Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"The Winship Cancer Institute of Emory Univ. (United States)","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032192226","display_name":"Jeffrey D. Bradley","orcid":"https://orcid.org/0000-0001-9305-7396"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jeffrey D. Bradley","raw_affiliation_strings":["The Winship Cancer Institute of Emory Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"The Winship Cancer Institute of Emory Univ. (United States)","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026088869","display_name":"Walter J. Curran","orcid":"https://orcid.org/0000-0002-7552-4453"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Walter J. Curran","raw_affiliation_strings":["The Winship Cancer Institute of Emory Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"The Winship Cancer Institute of Emory Univ. (United States)","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100365653","display_name":"Tian Liu","orcid":"https://orcid.org/0000-0002-5810-4318"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tian Liu","raw_affiliation_strings":["The Winship Cancer Institute of Emory Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"The Winship Cancer Institute of Emory Univ. (United States)","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100619090","display_name":"Xiaofeng Yang","orcid":"https://orcid.org/0000-0001-9023-5855"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaofeng Yang","raw_affiliation_strings":["The Winship Cancer Institute of Emory Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"The Winship Cancer Institute of Emory Univ. (United States)","institution_ids":["https://openalex.org/I150468666"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5049656223"],"corresponding_institution_ids":["https://openalex.org/I150468666"],"apc_list":null,"apc_paid":null,"fwci":0.1671,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.42268332,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"54","last_page":"54"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.9980000257492065,"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"}},"topics":[{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.9980000257492065,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9943000078201294,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9810000061988831,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/cone-beam-ct","display_name":"Cone beam ct","score":0.6489974856376648},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6183139681816101},{"id":"https://openalex.org/keywords/image-registration","display_name":"Image registration","score":0.606407642364502},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.601875364780426},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5749682188034058},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5731556415557861},{"id":"https://openalex.org/keywords/cone-beam-computed-tomography","display_name":"Cone beam computed tomography","score":0.45533862709999084},{"id":"https://openalex.org/keywords/computed-tomography","display_name":"Computed tomography","score":0.3119354844093323},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.15004703402519226},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.08310583233833313},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.07344445586204529}],"concepts":[{"id":"https://openalex.org/C3018399558","wikidata":"https://www.wikidata.org/wiki/Q1224951","display_name":"Cone beam ct","level":3,"score":0.6489974856376648},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6183139681816101},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.606407642364502},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.601875364780426},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5749682188034058},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5731556415557861},{"id":"https://openalex.org/C2779813781","wikidata":"https://www.wikidata.org/wiki/Q1224951","display_name":"Cone beam computed tomography","level":3,"score":0.45533862709999084},{"id":"https://openalex.org/C544519230","wikidata":"https://www.wikidata.org/wiki/Q32566","display_name":"Computed tomography","level":2,"score":0.3119354844093323},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.15004703402519226},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.08310583233833313},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.07344445586204529},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2580971","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2580971","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.6200000047683716}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3107520729","https://openalex.org/W4388840126","https://openalex.org/W2188736150","https://openalex.org/W4293073787","https://openalex.org/W2768843469","https://openalex.org/W2614950993","https://openalex.org/W2559007626","https://openalex.org/W4402945552","https://openalex.org/W2067918763","https://openalex.org/W3030757436"],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,54],"learning-based":[3],"method":[4,22,129],"to":[5,79],"register":[6],"4D":[7,29,72,88,99],"CBCT":[8,73,89],"images":[9],"from":[10,110],"different":[11],"respiratory":[12],"phases.":[13],"An":[14],"unsupervised":[15],"spatial":[16],"transformation":[17],"network":[18],"(STN)-based":[19],"deformable":[20],"registration":[21],"is":[23,39,58,123],"introduced":[24],"for":[25,60,93,137],"registering":[26],"phases":[27,109],"of":[28],"CBCT.":[30],"Namely,":[31],"no":[32],"ground":[33],"truth":[34],"deformation":[35],"vector":[36],"filed":[37],"(DVF)":[38],"needed":[40],"during":[41,141],"training.":[42],"To":[43,62],"avoid":[44],"the":[45,51,64,81,96],"scatter":[46],"artifact":[47],"effect":[48],"while":[49],"learning":[50],"trainable":[52],"parameters,":[53],"structural":[55],"similarity-based":[56],"loss":[57],"used":[59,78,92,102,114],"supervision.":[61],"evaluate":[63,80],"proposed":[65,82,128],"method,":[66],"we":[67],"retrospectively":[68],"investigate":[69],"20":[70],"lung":[71],"datasets.":[74],"Five-fold":[75],"cross-validation":[76],"was":[77],"method.":[83],"During":[84,105],"each":[85,107],"experiment,":[86],"16":[87],"datasets":[90],"were":[91,101,113],"training":[94],"and":[95,117],"rest":[97],"4":[98],"CBCTs":[100],"as":[103,115],"testing.":[104],"training,":[106],"two":[108],"one":[111],"patient":[112],"moving":[116],"fixed":[118],"images.":[119],"The":[120,127],"average":[121],"TRE":[122],"1.67":[124],"±3.30":[125],"mm.":[126],"has":[130],"great":[131],"potential":[132],"in":[133],"quantifying":[134],"tumor":[135],"trajectory":[136],"making":[138],"clinical":[139],"decision":[140],"radiation":[142],"therapy.":[143]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}