{"id":"https://openalex.org/W2768224069","doi":"https://doi.org/10.1109/tmi.2017.2777870","title":"Online Robust Projective Dictionary Learning: Shape Modeling for MR-TRUS Registration","display_name":"Online Robust Projective Dictionary Learning: Shape Modeling for MR-TRUS Registration","publication_year":2017,"publication_date":"2017-11-27","ids":{"openalex":"https://openalex.org/W2768224069","doi":"https://doi.org/10.1109/tmi.2017.2777870","mag":"2768224069","pmid":"https://pubmed.ncbi.nlm.nih.gov/29610082"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2017.2777870","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2017.2777870","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5100784220","display_name":"Yi Wang","orcid":"https://orcid.org/0000-0002-9013-7232"},"institutions":[{"id":"https://openalex.org/I4210145292","display_name":"Shenzhen University Health Science Center","ror":"https://ror.org/04yjbr930","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210145292"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yi Wang","raw_affiliation_strings":["National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I4210145292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022441060","display_name":"Qingqing Zheng","orcid":"https://orcid.org/0000-0001-7726-1901"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Qingqing Zheng","raw_affiliation_strings":["Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032708386","display_name":"Pheng\u2010Ann Heng","orcid":"https://orcid.org/0000-0003-3055-5034"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Pheng Ann Heng","raw_affiliation_strings":["Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100784220"],"corresponding_institution_ids":["https://openalex.org/I4210145292"],"apc_list":null,"apc_paid":null,"fwci":1.6617,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.88428969,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"37","issue":"4","first_page":"1067","last_page":"1078"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.9868999719619751,"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/T10727","display_name":"Ultrasound Imaging and Elastography","score":0.9664000272750854,"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/computer-science","display_name":"Computer science","score":0.7232440114021301},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6541405916213989},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6272778511047363},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5417526364326477},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.4840256869792938},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.46116939187049866},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4487060308456421},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4335736632347107},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4148273169994354},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3353957235813141},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1472403109073639}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7232440114021301},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6541405916213989},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6272778511047363},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5417526364326477},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.4840256869792938},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.46116939187049866},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4487060308456421},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4335736632347107},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4148273169994354},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3353957235813141},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1472403109073639},{"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},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011467","descriptor_name":"Prostate","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D011467","descriptor_name":"Prostate","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D011467","descriptor_name":"Prostate","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D011471","descriptor_name":"Prostatic Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D011471","descriptor_name":"Prostatic Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D011471","descriptor_name":"Prostatic Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D014463","descriptor_name":"Ultrasonography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D014463","descriptor_name":"Ultrasonography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D014463","descriptor_name":"Ultrasonography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D036761","descriptor_name":"Ultrasound, High-Intensity Focused, Transrectal","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D036761","descriptor_name":"Ultrasound, High-Intensity Focused, Transrectal","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D036761","descriptor_name":"Ultrasound, High-Intensity Focused, Transrectal","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/tmi.2017.2777870","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2017.2777870","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},{"id":"pmid:29610082","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/29610082","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on medical imaging","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.8799999952316284}],"awards":[{"id":"https://openalex.org/G1390094623","display_name":null,"funder_award_id":"ITT/007/16GP","funder_id":"https://openalex.org/F4320324196","funder_display_name":"Innovation and Technology Commission - Hong Kong"},{"id":"https://openalex.org/G3208008608","display_name":null,"funder_award_id":"61701312","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G444845467","display_name":null,"funder_award_id":"61571304","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5622395626","display_name":null,"funder_award_id":"KQTD2016053112051497","funder_id":"https://openalex.org/F4320335790","funder_display_name":"Shenzhen Peacock Plan"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324196","display_name":"Innovation and Technology Commission - Hong Kong","ror":"https://ror.org/04vf9tr09"},{"id":"https://openalex.org/F4320335790","display_name":"Shenzhen Peacock Plan","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W114517082","https://openalex.org/W656835260","https://openalex.org/W1896190717","https://openalex.org/W1906917243","https://openalex.org/W1966901658","https://openalex.org/W2004377710","https://openalex.org/W2005876975","https://openalex.org/W2011148084","https://openalex.org/W2018079976","https://openalex.org/W2021345820","https://openalex.org/W2029115635","https://openalex.org/W2029256820","https://openalex.org/W2057775191","https://openalex.org/W2093922090","https://openalex.org/W2099474347","https://openalex.org/W2105732805","https://openalex.org/W2106033751","https://openalex.org/W2110872054","https://openalex.org/W2114122776","https://openalex.org/W2119883478","https://openalex.org/W2121058967","https://openalex.org/W2122313934","https://openalex.org/W2128409098","https://openalex.org/W2129812935","https://openalex.org/W2132467081","https://openalex.org/W2134012543","https://openalex.org/W2134236847","https://openalex.org/W2139989322","https://openalex.org/W2146373036","https://openalex.org/W2150796457","https://openalex.org/W2157814660","https://openalex.org/W2159158140","https://openalex.org/W2160547390","https://openalex.org/W2163112044","https://openalex.org/W2163398148","https://openalex.org/W2164051596","https://openalex.org/W2171490473","https://openalex.org/W2176723361","https://openalex.org/W2235523093","https://openalex.org/W2280845481","https://openalex.org/W2412147887","https://openalex.org/W2583914614","https://openalex.org/W2594119921","https://openalex.org/W2606057727","https://openalex.org/W3145074154","https://openalex.org/W4255655703","https://openalex.org/W6676014314","https://openalex.org/W6733344817"],"related_works":["https://openalex.org/W2541791370","https://openalex.org/W2035976912","https://openalex.org/W2539272015","https://openalex.org/W3094187672","https://openalex.org/W2594663467","https://openalex.org/W2165670234","https://openalex.org/W2921707373","https://openalex.org/W4386597354","https://openalex.org/W2915550111","https://openalex.org/W198500362"],"abstract_inverted_index":{"Robust":[0],"and":[1,22,60,78,94,117,119,130,162,181],"effective":[2],"shape":[3,18,23,33,68,141,164,190],"prior":[4,69,142,191],"modeling":[5,165,178],"from":[6],"a":[7,13,39,64,76,183],"set":[8],"of":[9,85,128,146,189],"training":[10,87],"data":[11],"remains":[12],"challenging":[14],"task,":[15],"since":[16],"the":[17,53,57,82,86,92,98,103,111,115,144,167,187],"variation":[19],"is":[20,47,107,120,136,175],"complicated,":[21],"models":[24],"should":[25],"preserve":[26],"local":[27],"details":[28],"as":[29,31],"well":[30],"handle":[32,114],"noises.":[34],"To":[35],"address":[36],"these":[37],"challenges,":[38],"novel":[40],"robust":[41,77,163],"projective":[42],"dictionary":[43,61,80],"learning":[44,62],"(RPDL)":[45],"scheme":[46],"proposed":[48,104,134,172],"in":[49,122],"this":[50],"paper.":[51],"Specifically,":[52],"RPDL":[54,105,173],"method":[55,135,158,174],"integrates":[56],"dimension":[58],"reduction":[59],"into":[63],"unified":[65],"framework":[66,125],"for":[67,143,177,186],"modeling,":[70],"which":[71],"can":[72],"not":[73],"only":[74],"learn":[75],"representative":[79],"with":[81],"energy":[83],"preservation":[84],"data,":[88],"but":[89],"also":[90],"reduce":[91],"dimensionality":[93],"computational":[95],"cost":[96],"via":[97],"subspace":[99],"learning.":[100],"In":[101],"addition,":[102],"algorithm":[106],"regularized":[108],"by":[109],"using":[110],"norm":[112],"to":[113,138],"outliers":[116],"noises,":[118],"embedded":[121],"an":[123],"online":[124],"so":[126],"that":[127,156],"memory":[129],"time":[131],"efficiency.":[132],"The":[133,152,171],"employed":[137],"model":[139],"prostate":[140],"application":[145],"magnetic":[147],"resonance":[148],"transrectal":[149],"ultrasound":[150],"registration.":[151],"experimental":[153],"results":[154],"demonstrate":[155],"our":[157],"provides":[159],"more":[160],"accurate":[161],"than":[166],"state-of-the-art":[168],"methods":[169],"do.":[170],"applicable":[176],"other":[179],"organs,":[180],"hence,":[182],"general":[184],"solution":[185],"problem":[188],"modeling.":[192]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}