{"id":"https://openalex.org/W2329840665","doi":"https://doi.org/10.1117/12.2216430","title":"A MRI-CT prostate registration using sparse representation technique","display_name":"A MRI-CT prostate registration using sparse representation technique","publication_year":2016,"publication_date":"2016-03-18","ids":{"openalex":"https://openalex.org/W2329840665","doi":"https://doi.org/10.1117/12.2216430","mag":"2329840665"},"language":"en","primary_location":{"id":"doi:10.1117/12.2216430","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2216430","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","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/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":true,"raw_author_name":"Xiaofeng Yang","raw_affiliation_strings":["Winship Cancer Institute, Emory Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"Winship Cancer Institute, Emory Univ. (United States)","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112746616","display_name":"Ashesh B. Jani","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":"Ashesh B. Jani","raw_affiliation_strings":["Winship Cancer Institute, Emory Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"Winship Cancer Institute, Emory Univ. (United States)","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101454375","display_name":"Peter J. Rossi","orcid":"https://orcid.org/0000-0003-1521-1225"},"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":"Peter J. Rossi","raw_affiliation_strings":["Winship Cancer Institute, Emory Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"Winship Cancer Institute, Emory Univ. (United States)","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068714594","display_name":"Hui Mao","orcid":"https://orcid.org/0000-0002-0147-6022"},"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":"Hui Mao","raw_affiliation_strings":["Winship Cancer Institute, Emory Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"Winship Cancer Institute, 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":["Winship Cancer Institute, Emory Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"Winship Cancer Institute, Emory Univ. (United States)","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100365671","display_name":"Tian Liu","orcid":"https://orcid.org/0009-0007-8567-3608"},"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":["Winship Cancer Institute, Emory Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"Winship Cancer Institute, Emory Univ. (United States)","institution_ids":["https://openalex.org/I150468666"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100619090"],"corresponding_institution_ids":["https://openalex.org/I150468666"],"apc_list":null,"apc_paid":null,"fwci":0.8547,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.73251413,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"9786","issue":null,"first_page":"978627","last_page":"978627"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9987000226974487,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.996999979019165,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7299318313598633},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7236839532852173},{"id":"https://openalex.org/keywords/image-registration","display_name":"Image registration","score":0.5653308629989624},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5640112161636353},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.5126554369926453},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41991299390792847},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4116554260253906},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.41076621413230896}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7299318313598633},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7236839532852173},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.5653308629989624},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5640112161636353},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.5126554369926453},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41991299390792847},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4116554260253906},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.41076621413230896},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2216430","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2216430","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320333204","display_name":"Winship Cancer Institute","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W95913851","https://openalex.org/W1006446162","https://openalex.org/W1970928383","https://openalex.org/W1979940301","https://openalex.org/W1982311990","https://openalex.org/W1995408015","https://openalex.org/W1996845736","https://openalex.org/W1998710995","https://openalex.org/W2010587020","https://openalex.org/W2014914090","https://openalex.org/W2016232374","https://openalex.org/W2023451960","https://openalex.org/W2028108415","https://openalex.org/W2033170596","https://openalex.org/W2042730326","https://openalex.org/W2073710995","https://openalex.org/W2080184398","https://openalex.org/W2080830831","https://openalex.org/W2098226918","https://openalex.org/W2098815853","https://openalex.org/W2103857226","https://openalex.org/W2110394359","https://openalex.org/W2113576511","https://openalex.org/W2129594229","https://openalex.org/W2135046866","https://openalex.org/W2137013440","https://openalex.org/W2148673597","https://openalex.org/W2158018331","https://openalex.org/W2764668828","https://openalex.org/W4234432481","https://openalex.org/W4237247691","https://openalex.org/W4245795235","https://openalex.org/W4247603435","https://openalex.org/W6661221832","https://openalex.org/W6679274309","https://openalex.org/W6680156768","https://openalex.org/W6683592866","https://openalex.org/W6744914595"],"related_works":["https://openalex.org/W2062195135","https://openalex.org/W2130187411","https://openalex.org/W2795079307","https://openalex.org/W2793058541","https://openalex.org/W2387058352","https://openalex.org/W1983629434","https://openalex.org/W2004814108","https://openalex.org/W2890544631","https://openalex.org/W2511090434","https://openalex.org/W1964749215"],"abstract_inverted_index":{"<strong>Purpose</strong>:":[0],"To":[1],"develop":[2],"a":[3,42,113,137,151,228,279,314,373,420],"new":[4,138,374],"MRI-CT":[5,216,308],"prostate":[6,16,36,91,375,425],"registration":[7,292,309,339,347,363,377,397],"using":[8,46,327],"patch-based":[9],"deformation":[10,34,61,122,255,281,409],"prediction":[11],"framework":[12],"to":[13,31,97,112,245,252,277,289,303],"improve":[14],"MRI-guided":[15],"radiotherapy":[17],"by":[18,45,227],"incorporating":[19],"multiparametric":[20],"MRI":[21,37,302,333,411],"into":[22],"planning":[23],"CT":[24,39,100,107,115,129,146,164,174,271,304,335,413],"images.":[25,217,336],"<strong>Methods</strong>:":[26],"The":[27,320,349,395],"main":[28],"contribution":[29],"is":[30,284,416],"estimate":[32],"the":[33,47,59,79,83,87,98,120,132,143,158,172,178,183,191,195,202,209,219,236,241,246,250,254,257,265,287,291,295,343,352,359],"between":[35,410],"and":[38,82,102,106,128,208,334,387,403,412,415],"images":[40,93,101,108],"in":[41,74,171,201,235,249,331],"patch-wise":[43,64],"fashion":[44],"sparse":[48,243],"representation":[49],"technique.":[50],"We":[51,370],"assume":[52],"that":[53],"two":[54,72],"image":[55,141,179,206,221,233,260],"patches":[56,207,234],"should":[57],"follow":[58],"same":[60,144,242,266],"if":[62],"their":[63],"appearance":[65],"patterns":[66],"are":[67,71,94,109],"similar.":[68],"Specifically,":[69],"there":[70],"stages":[73],"our":[75,323],"proposed":[76,338,353,396],"framework,":[77],"i.e.,":[78],"training":[80,88,104,126,214,232],"stage":[81],"application":[84,133],"stage.":[85],"In":[86,131],"stage,":[89,134],"each":[90,125,168,199,269],"MR":[92,105,127,140,259],"carefully":[95,110],"registered":[96,111],"corresponding":[99],"all":[103],"selected":[114],"template.":[116],"Thus,":[117],"we":[118,148,176,188,239,263,274],"obtain":[119],"dense":[121,280],"field":[123],"for":[124,135,167,194,256,268,419],"image.":[130,165,305],"registering":[136],"subject":[139,145,163,173,220,258,270],"with":[142,313,342,391],"image,":[147,175],"first":[149],"select":[150],"small":[152,297],"number":[153,421],"of":[154,161,205,231,299,317,322,351,406,422],"key":[155,169,185,272],"points":[156],"at":[157,182],"distinctive":[159],"regions":[160],"this":[162],"Then,":[166,187],"point":[170,197],"extract":[177],"patch,":[180],"centered":[181],"underlying":[184,196],"point.":[186],"adaptively":[189],"construct":[190],"coupled":[192],"dictionary":[193,203,251],"where":[198,238],"atom":[200],"consists":[204],"respective":[210,247],"deformations":[211,248,300],"obtained":[212],"from":[213,301],"pair-wise":[215],"Next,":[218],"patch":[222],"can":[223],"be":[224],"sparsely":[225],"represented":[226],"linear":[229],"combination":[230],"dictionary,":[237,382],"apply":[240],"coefficients":[244],"predict":[253],"patch.":[261],"After":[262],"repeat":[264],"procedure":[267],"point,":[273],"use":[275],"B-splines":[276],"interpolate":[278],"field,":[282],"which":[283],"used":[285,361],"as":[286],"initialization":[288],"allow":[290],"algorithm":[293],"estimating":[294,407],"remaining":[296],"segment":[298],"<strong>Results</strong>:":[306],"Our":[307,337],"technique":[310],"was":[311,325,340,355],"validated":[312,388],"clinical":[315,385],"study":[316],"10":[318],"patients.":[319],"accuracy":[321,350,390],"approach":[324,378],"assessed":[326],"some":[328,392],"identified":[329,393],"landmarks":[330],"both":[332],"compared":[341],"current":[344],"free-form-deformation":[345],"(FFD)-based":[346],"method.":[348],"method":[354,398],"significantly":[356],"higher":[357],"than":[358],"commonly":[360],"FFD-based":[362],"utilizing":[364],"normalized":[365],"mutual":[366],"information":[367],"(NMI).":[368],"<strong>Conclusions</strong>:":[369],"have":[371],"developed":[372],"MR-CT":[376],"based":[379],"on":[380],"patch-deformation":[381],"demonstrated":[383],"its":[384,389],"feasibility,":[386],"landmarks.":[394],"may":[399],"provide":[400],"an":[401],"accurate":[402],"robust":[404],"means":[405],"prostate-gland":[408],"scans,":[414],"therefore":[417],"well-suited":[418],"MR-targeted":[423],"CT-based":[424],"radiotherapy.":[426]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}