{"id":"https://openalex.org/W2120015570","doi":"https://doi.org/10.1186/1687-5281-2011-15","title":"Rician nonlocal means denoising for MR images using nonparametric principal component analysis","display_name":"Rician nonlocal means denoising for MR images using nonparametric principal component analysis","publication_year":2011,"publication_date":"2011-10-14","ids":{"openalex":"https://openalex.org/W2120015570","doi":"https://doi.org/10.1186/1687-5281-2011-15","mag":"2120015570"},"language":"en","primary_location":{"id":"doi:10.1186/1687-5281-2011-15","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1687-5281-2011-15","pdf_url":"https://jivp-eurasipjournals.springeropen.com/counter/pdf/10.1186/1687-5281-2011-15","source":{"id":"https://openalex.org/S153767265","display_name":"EURASIP Journal on Image and Video Processing","issn_l":"1687-5176","issn":["1687-5176","1687-5281"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Image and Video Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://jivp-eurasipjournals.springeropen.com/counter/pdf/10.1186/1687-5281-2011-15","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100389864","display_name":"Dong Wook Kim","orcid":"https://orcid.org/0000-0002-5819-9783"},"institutions":[{"id":"https://openalex.org/I161217753","display_name":"Busan National University of Education","ror":"https://ror.org/01rf04680","country_code":"KR","type":"education","lineage":["https://openalex.org/I161217753"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dong Wook Kim","raw_affiliation_strings":["Department of Statistics, Busan National University, Busan, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Busan National University, Busan, Korea","institution_ids":["https://openalex.org/I161217753"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041130636","display_name":"Chansoo Kim","orcid":"https://orcid.org/0000-0002-7594-9072"},"institutions":[{"id":"https://openalex.org/I206597221","display_name":"Kongju National University","ror":"https://ror.org/0373nm262","country_code":"KR","type":"education","lineage":["https://openalex.org/I206597221"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chansoo Kim","raw_affiliation_strings":["Department of Applied Mathematics, Kongju National University, Gongju, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Applied Mathematics, Kongju National University, Gongju, Korea","institution_ids":["https://openalex.org/I206597221"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100439126","display_name":"Dong Hee Kim","orcid":"https://orcid.org/0000-0002-9023-6847"},"institutions":[{"id":"https://openalex.org/I161217753","display_name":"Busan National University of Education","ror":"https://ror.org/01rf04680","country_code":"KR","type":"education","lineage":["https://openalex.org/I161217753"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dong Hee Kim","raw_affiliation_strings":["Department of Statistics, Busan National University, Busan, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Busan National University, Busan, Korea","institution_ids":["https://openalex.org/I161217753"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038374190","display_name":"Dong Hoon Lim","orcid":"https://orcid.org/0000-0002-7186-4522"},"institutions":[{"id":"https://openalex.org/I189442560","display_name":"Gyeongsang National University","ror":"https://ror.org/00saywf64","country_code":"KR","type":"education","lineage":["https://openalex.org/I189442560"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Dong Hoon Lim","raw_affiliation_strings":["Department of Information Statistics and RINS, Gyeongsang National University, Jinju, 660-701, Korea","Department of Information Statistics and RINS, Gyeongsang National University, Jinju, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Statistics and RINS, Gyeongsang National University, Jinju, 660-701, Korea","institution_ids":["https://openalex.org/I189442560"]},{"raw_affiliation_string":"Department of Information Statistics and RINS, Gyeongsang National University, Jinju, Korea","institution_ids":["https://openalex.org/I189442560"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5038374190"],"corresponding_institution_ids":["https://openalex.org/I189442560"],"apc_list":{"value":1665,"currency":"USD","value_usd":1665},"apc_paid":{"value":1665,"currency":"USD","value_usd":1665},"fwci":0.5482,"has_fulltext":true,"cited_by_count":23,"citation_normalized_percentile":{"value":0.74055493,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"2011","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":1.0,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.993399977684021,"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/rician-fading","display_name":"Rician fading","score":0.8166869282722473},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6271541118621826},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.6239805221557617},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6199520230293274},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6179423332214355},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5814850330352783},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.58058100938797},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5508373975753784},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.5227834582328796},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.4636593461036682},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.42020153999328613},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.37770047783851624},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.20712903141975403},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.18248844146728516},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.17882955074310303},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07710012793540955}],"concepts":[{"id":"https://openalex.org/C60472773","wikidata":"https://www.wikidata.org/wiki/Q7331156","display_name":"Rician fading","level":4,"score":0.8166869282722473},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6271541118621826},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.6239805221557617},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6199520230293274},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6179423332214355},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5814850330352783},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.58058100938797},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5508373975753784},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.5227834582328796},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.4636593461036682},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.42020153999328613},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37770047783851624},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.20712903141975403},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.18248844146728516},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.17882955074310303},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07710012793540955},{"id":"https://openalex.org/C81978471","wikidata":"https://www.wikidata.org/wiki/Q1196572","display_name":"Fading","level":3,"score":0.0},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1186/1687-5281-2011-15","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1687-5281-2011-15","pdf_url":"https://jivp-eurasipjournals.springeropen.com/counter/pdf/10.1186/1687-5281-2011-15","source":{"id":"https://openalex.org/S153767265","display_name":"EURASIP Journal on Image and Video Processing","issn_l":"1687-5176","issn":["1687-5176","1687-5281"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Image and Video Processing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1186/1687-5281-2011-15","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1687-5281-2011-15","pdf_url":"https://jivp-eurasipjournals.springeropen.com/counter/pdf/10.1186/1687-5281-2011-15","source":{"id":"https://openalex.org/S153767265","display_name":"EURASIP Journal on Image and Video Processing","issn_l":"1687-5176","issn":["1687-5176","1687-5281"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Image and Video Processing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2120015570.pdf","grobid_xml":"https://content.openalex.org/works/W2120015570.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W1899329334","https://openalex.org/W1977775666","https://openalex.org/W2011344206","https://openalex.org/W2018764772","https://openalex.org/W2041963641","https://openalex.org/W2059784307","https://openalex.org/W2087329389","https://openalex.org/W2088477804","https://openalex.org/W2096413230","https://openalex.org/W2097073572","https://openalex.org/W2123145781","https://openalex.org/W2128265222","https://openalex.org/W2132140814","https://openalex.org/W2133097426","https://openalex.org/W2133665775","https://openalex.org/W2136396015","https://openalex.org/W2138018102","https://openalex.org/W2142592339","https://openalex.org/W2151952539","https://openalex.org/W2156668482","https://openalex.org/W2160172778","https://openalex.org/W2161037052","https://openalex.org/W2184898757","https://openalex.org/W2991651364"],"related_works":["https://openalex.org/W2146680430","https://openalex.org/W2100999214","https://openalex.org/W1973317750","https://openalex.org/W1641214707","https://openalex.org/W2166688772","https://openalex.org/W2170880428","https://openalex.org/W2590769158","https://openalex.org/W2096957949","https://openalex.org/W1607978590","https://openalex.org/W2076800748"],"abstract_inverted_index":{"Abstract":[0],"Denoising":[1],"is":[2,13,41,51,85,127,175],"always":[3],"a":[4,32,52,60,111],"challenging":[5],"problem":[6],"in":[7,29,80,93,131,137,181],"magnetic":[8],"resonance":[9],"imaging":[10],"(MRI)":[11],"and":[12,18,25,44,90,96,117,153,183],"important":[14],"for":[15,76,104,110,125],"clinical":[16],"diagnosis":[17],"computerized":[19],"analysis,":[20],"such":[21],"as":[22,134,136],"tissue":[23],"classification":[24],"segmentation.":[26],"The":[27,167],"noise":[28,40,50,78,133,189],"MRI":[30],"has":[31],"Rician":[33,39,77,165],"distribution.":[34],"Unlike":[35],"additive":[36],"Gaussian":[37],"noise,":[38],"signal":[42,47],"dependent,":[43],"separating":[45],"the":[46,49,64,87,120,132,142,145,149,154,172,176],"from":[48],"difficult":[53],"task.":[54],"In":[55],"this":[56],"paper,":[57],"we":[58,140],"propose":[59],"useful":[61],"alternative":[62,84],"of":[63,115,122,144,164],"nonlocal":[65],"mean":[66],"(NLM)":[67],"filter":[68,147,152,156,174],"that":[69,119,171],"uses":[70],"nonparametric":[71],"principal":[72,123],"component":[73],"analysis":[74],"(NPCA)":[75],"reduction":[79],"MR":[81,158],"images.":[82,138],"This":[83],"called":[86],"NPCA-NLM":[88,173],"filter,":[89],"it":[91],"results":[92,169],"improved":[94],"accuracy":[95],"computational":[97],"performance.":[98],"We":[99],"present":[100],"an":[101],"applicable":[102],"method":[103],"estimating":[105],"smoothing":[106],"kernel":[107],"width":[108],"parameters":[109],"much":[112],"larger":[113],"set":[114],"images":[116,159],"demonstrate":[118],"number":[121],"components":[124],"NPCA":[126],"robust":[128,178],"to":[129,179],"variations":[130,180],"well":[135],"Finally,":[139],"investigate":[141],"performance":[143,186],"proposed":[146],"with":[148,161],"standard":[150],"NLM":[151],"PCA-NLM":[155],"on":[157],"corrupted":[160],"various":[162],"levels":[163,190],"noise.":[166],"experimental":[168],"indicate":[170],"most":[177],"images,":[182],"shows":[184],"good":[185],"at":[187],"all":[188],"tested.":[191]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}