{"id":"https://openalex.org/W2104024054","doi":"https://doi.org/10.1109/83.704309","title":"Quantification and segmentation of brain tissues from MR images: a probabilistic neural network approach","display_name":"Quantification and segmentation of brain tissues from MR images: a probabilistic neural network approach","publication_year":1998,"publication_date":"1998-01-01","ids":{"openalex":"https://openalex.org/W2104024054","doi":"https://doi.org/10.1109/83.704309","mag":"2104024054","pmid":"https://pubmed.ncbi.nlm.nih.gov/18172510"},"language":"en","primary_location":{"id":"doi:10.1109/83.704309","is_oa":false,"landing_page_url":"https://doi.org/10.1109/83.704309","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/2171050","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100417892","display_name":"Yue Wang","orcid":"https://orcid.org/0009-0004-7050-9811"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]},{"id":"https://openalex.org/I168959743","display_name":"University of America","ror":"https://ror.org/03s0c9350","country_code":"US","type":"education","lineage":["https://openalex.org/I168959743"]},{"id":"https://openalex.org/I184565670","display_name":"Georgetown University","ror":"https://ror.org/05vzafd60","country_code":"US","type":"education","lineage":["https://openalex.org/I184565670"]},{"id":"https://openalex.org/I84470341","display_name":"Catholic University of America","ror":"https://ror.org/047yk3s18","country_code":"US","type":"education","lineage":["https://openalex.org/I84470341"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yue Wang","raw_affiliation_strings":["Y. Wang is with the Department of Electrical Engineering and Computer Science, The Catholic University of America, Washington, DC 20064 USA, and is affiliated with the Department of Radiology, Georgetown University School of Medicine, Washington, DC 20007 USA (e-mail:  wang@pluto.ee.cua.edu )","Department of Electrical Engineering and Computer Science, Catholic University of America, Washington D.C., DC, USA","Department of Radiology, Georgia Institute of Technology, Washington D.C., DC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Y. Wang is with the Department of Electrical Engineering and Computer Science, The Catholic University of America, Washington, DC 20064 USA, and is affiliated with the Department of Radiology, Georgetown University School of Medicine, Washington, DC 20007 USA (e-mail:  wang@pluto.ee.cua.edu )","institution_ids":["https://openalex.org/I184565670","https://openalex.org/I168959743"]},{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Catholic University of America, Washington D.C., DC, USA","institution_ids":["https://openalex.org/I84470341"]},{"raw_affiliation_string":"Department of Radiology, Georgia Institute of Technology, Washington D.C., DC, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5098372852","display_name":"T. Adah","orcid":null},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"T. Adah","raw_affiliation_strings":["Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County, Baltimore, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County, Baltimore, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072714962","display_name":"Sun\u2010Yuan Kung","orcid":"https://orcid.org/0000-0002-7314-0720"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sun-Yuan Kung","raw_affiliation_strings":["Department of Electrical Engineering, Princeton University, Princeton, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Princeton University, Princeton, NJ, USA","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041846479","display_name":"Z Szab\u00f2","orcid":"https://orcid.org/0009-0003-8524-4994"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Z. Szabo","raw_affiliation_strings":["Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.5544,"has_fulltext":false,"cited_by_count":97,"citation_normalized_percentile":{"value":0.96768435,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"7","issue":"8","first_page":"1165","last_page":"1181"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9997000098228455,"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/T10320","display_name":"Neural Networks and Applications","score":0.9997000098228455,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9965000152587891,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9961000084877014,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7523949146270752},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.7300499081611633},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.6796757578849792},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6722249388694763},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.667438805103302},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6667119264602661},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6418232321739197},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5433490872383118},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5090331435203552},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.49442338943481445},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.46831828355789185},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.275674968957901}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7523949146270752},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.7300499081611633},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.6796757578849792},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6722249388694763},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.667438805103302},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6667119264602661},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6418232321739197},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5433490872383118},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5090331435203552},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.49442338943481445},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.46831828355789185},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.275674968957901},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/83.704309","is_oa":false,"landing_page_url":"https://doi.org/10.1109/83.704309","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},{"id":"pmid:18172510","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/18172510","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 image processing : a publication of the IEEE Signal Processing Society","raw_type":null},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.40.581","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.40.581","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.engr.umbc.edu/~adali/papers/ip98.ps","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.63.8421","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.63.8421","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://eivind.imm.dtu.dk/teaching/BiomedImg/IP98.pdf","raw_type":"text"},{"id":"pmh:oai:pubmedcentral.nih.gov:2171050","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/2171050","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Trans Image Process","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:2171050","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/2171050","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Trans Image Process","raw_type":"Text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3063196560","display_name":null,"funder_award_id":"R01 AG014400","funder_id":"https://openalex.org/F4320337337","funder_display_name":"National Institute on Aging"},{"id":"https://openalex.org/G6708278979","display_name":null,"funder_award_id":"R01 AA011653","funder_id":"https://openalex.org/F4320337330","funder_display_name":"National Institute on Alcohol Abuse and Alcoholism"},{"id":"https://openalex.org/G6848224842","display_name":null,"funder_award_id":"R01 DK050183","funder_id":"https://openalex.org/F4320337357","funder_display_name":"National Institute of Diabetes and Digestive and Kidney Diseases"}],"funders":[{"id":"https://openalex.org/F4320310223","display_name":"Georgetown University","ror":"https://ror.org/05vzafd60"},{"id":"https://openalex.org/F4320337330","display_name":"National Institute on Alcohol Abuse and Alcoholism","ror":"https://ror.org/02jzrsm59"},{"id":"https://openalex.org/F4320337337","display_name":"National Institute on Aging","ror":"https://ror.org/049v75w11"},{"id":"https://openalex.org/F4320337357","display_name":"National Institute of Diabetes and Digestive and Kidney Diseases","ror":"https://ror.org/00adh9b73"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W168136078","https://openalex.org/W1575930425","https://openalex.org/W1605531054","https://openalex.org/W1840338487","https://openalex.org/W1877469487","https://openalex.org/W1887012233","https://openalex.org/W1971748236","https://openalex.org/W1981367467","https://openalex.org/W1990086843","https://openalex.org/W2002011878","https://openalex.org/W2021868098","https://openalex.org/W2028900159","https://openalex.org/W2032558547","https://openalex.org/W2042797350","https://openalex.org/W2043803464","https://openalex.org/W2063125200","https://openalex.org/W2072582127","https://openalex.org/W2073547849","https://openalex.org/W2076118331","https://openalex.org/W2096710051","https://openalex.org/W2098900497","https://openalex.org/W2099111195","https://openalex.org/W2104667325","https://openalex.org/W2106596127","https://openalex.org/W2107792892","https://openalex.org/W2108843657","https://openalex.org/W2111489177","https://openalex.org/W2118439356","https://openalex.org/W2124229187","https://openalex.org/W2124776405","https://openalex.org/W2126397022","https://openalex.org/W2131034055","https://openalex.org/W2132513126","https://openalex.org/W2134199473","https://openalex.org/W2139300463","https://openalex.org/W2140392457","https://openalex.org/W2142472957","https://openalex.org/W2142635246","https://openalex.org/W2146437028","https://openalex.org/W2146959525","https://openalex.org/W2151413156","https://openalex.org/W2151994846","https://openalex.org/W2155779316","https://openalex.org/W2158595748","https://openalex.org/W2160208155","https://openalex.org/W2163599171","https://openalex.org/W2166502205","https://openalex.org/W2166698530","https://openalex.org/W2169061716","https://openalex.org/W2171765626","https://openalex.org/W2797746357","https://openalex.org/W4247923313","https://openalex.org/W4252028749"],"related_works":["https://openalex.org/W2107628111","https://openalex.org/W2085033728","https://openalex.org/W4285411112","https://openalex.org/W2171299904","https://openalex.org/W2394004323","https://openalex.org/W2345647014","https://openalex.org/W2201192772","https://openalex.org/W3136891595","https://openalex.org/W2535030201","https://openalex.org/W1964819397"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,108],"probabilistic":[4,101,109],"neural":[5],"network":[6],"based":[7,133],"technique":[8,71],"for":[9,76],"unsupervised":[10],"quantification":[11,97],"and":[12,33,48,61,80,83,92,104,119,126],"segmentation":[13,106],"of":[14,56,64,89,122],"brain":[15,51],"tissues":[16,52],"from":[17],"magnetic":[18],"resonance":[19],"images.":[20],"It":[21],"is":[22,59,98],"shown":[23],"that":[24,41,127],"this":[25],"problem":[26,86],"can":[27],"be":[28,43],"solved":[29],"by":[30,100,107],"distribution":[31],"learning":[32],"relaxation":[34,111],"labeling,":[35],"resulting":[36],"in":[37,46,87],"an":[38],"efficient":[39,118],"method":[40],"may":[42],"particularly":[44],"useful":[45],"quantifying":[47],"segmenting":[49],"abnormal":[50],"where":[53],"the":[54,62,78,85,105,117,123,130],"number":[55],"tissue":[57,65],"types":[58,66],"unknown":[60],"distributions":[63],"heavily":[67],"overlap.":[68],"The":[69,96,113],"new":[70,124],"uses":[72],"suitable":[73],"statistical":[74],"models":[75],"both":[77],"pixel":[79],"context":[81],"images":[82],"formulates":[84],"terms":[88],"model-histogram":[90],"fitting":[91],"global":[93],"consistency":[94],"labeling.":[95],"achieved":[99],"self-organizing":[102],"mixtures":[103],"constraint":[110],"network.":[112],"experimental":[114],"results":[115],"show":[116],"robust":[120],"performance":[121],"algorithm":[125],"it":[128],"outperforms":[129],"conventional":[131],"classification":[132],"approaches.":[134]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":4},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":4}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}