{"id":"https://openalex.org/W2097739662","doi":"https://doi.org/10.1109/isbi.2012.6235610","title":"Manifold-constrained embeddings for the detection of white matter lesions in brain MRI","display_name":"Manifold-constrained embeddings for the detection of white matter lesions in brain MRI","publication_year":2012,"publication_date":"2012-05-01","ids":{"openalex":"https://openalex.org/W2097739662","doi":"https://doi.org/10.1109/isbi.2012.6235610","mag":"2097739662","pmid":"https://pubmed.ncbi.nlm.nih.gov/24443675"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2012.6235610","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2012.6235610","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 9th IEEE International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-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/3892901","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039187492","display_name":"Samuel Kadoury","orcid":"https://orcid.org/0000-0002-3048-4291"},"institutions":[{"id":"https://openalex.org/I4210131230","display_name":"Philips (United States)","ror":"https://ror.org/03kw6wr76","country_code":"US","type":"company","lineage":["https://openalex.org/I4210122849","https://openalex.org/I4210131230"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Samuel Kadoury","raw_affiliation_strings":["Philips Research North America, Briarcliff Manor, NY, USA"],"affiliations":[{"raw_affiliation_string":"Philips Research North America, Briarcliff Manor, NY, USA","institution_ids":["https://openalex.org/I4210131230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029649151","display_name":"G\u00fcray Erus","orcid":"https://orcid.org/0000-0001-6633-4861"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guray Erus","raw_affiliation_strings":["SBIA, Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA"],"affiliations":[{"raw_affiliation_string":"SBIA, Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048652955","display_name":"Evangelia I. Zacharaki","orcid":"https://orcid.org/0000-0001-8228-0437"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Evangelia I. Zacharaki","raw_affiliation_strings":["School of Medicine, University of Patras, Greece"],"affiliations":[{"raw_affiliation_string":"School of Medicine, University of Patras, Greece","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077223134","display_name":"Nikos Paragios","orcid":"https://orcid.org/0000-0002-9668-4763"},"institutions":[{"id":"https://openalex.org/I216852786","display_name":"\u00c9cole Centrale Paris","ror":"https://ror.org/00v0y5771","country_code":"FR","type":"education","lineage":["https://openalex.org/I216852786"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Nikos Paragios","raw_affiliation_strings":["Center for Visual Computing, Ecole Centrale Paris, France"],"affiliations":[{"raw_affiliation_string":"Center for Visual Computing, Ecole Centrale Paris, France","institution_ids":["https://openalex.org/I216852786"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034999945","display_name":"Christos Davatzikos","orcid":"https://orcid.org/0000-0002-1025-8561"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christos Davatzikos","raw_affiliation_strings":["SBIA, Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA"],"affiliations":[{"raw_affiliation_string":"SBIA, Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5039187492"],"corresponding_institution_ids":["https://openalex.org/I4210131230"],"apc_list":null,"apc_paid":null,"fwci":0.2785,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.60139302,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"23","issue":null,"first_page":"562","last_page":"565"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9962000250816345,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9962000250816345,"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/T10057","display_name":"Face and Expression Recognition","score":0.9962000250816345,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9871000051498413,"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/hyperintensity","display_name":"Hyperintensity","score":0.6761246919631958},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6143571734428406},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6085758805274963},{"id":"https://openalex.org/keywords/nonlinear-dimensionality-reduction","display_name":"Nonlinear dimensionality reduction","score":0.606998860836029},{"id":"https://openalex.org/keywords/normality","display_name":"Normality","score":0.6000606417655945},{"id":"https://openalex.org/keywords/geodesic","display_name":"Geodesic","score":0.5807461142539978},{"id":"https://openalex.org/keywords/manifold","display_name":"Manifold (fluid mechanics)","score":0.4869600236415863},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.483960896730423},{"id":"https://openalex.org/keywords/white-matter","display_name":"White matter","score":0.47475937008857727},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4405045211315155},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.42793336510658264},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.4252641797065735},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4226028323173523},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.2694164514541626},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.24864250421524048},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.24461525678634644},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.2336103916168213},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.13968494534492493}],"concepts":[{"id":"https://openalex.org/C146638467","wikidata":"https://www.wikidata.org/wiki/Q10529587","display_name":"Hyperintensity","level":3,"score":0.6761246919631958},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6143571734428406},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6085758805274963},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.606998860836029},{"id":"https://openalex.org/C2776157432","wikidata":"https://www.wikidata.org/wiki/Q1375683","display_name":"Normality","level":2,"score":0.6000606417655945},{"id":"https://openalex.org/C165818556","wikidata":"https://www.wikidata.org/wiki/Q213488","display_name":"Geodesic","level":2,"score":0.5807461142539978},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.4869600236415863},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.483960896730423},{"id":"https://openalex.org/C2781192897","wikidata":"https://www.wikidata.org/wiki/Q822050","display_name":"White matter","level":3,"score":0.47475937008857727},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4405045211315155},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.42793336510658264},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.4252641797065735},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4226028323173523},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.2694164514541626},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.24864250421524048},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.24461525678634644},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.2336103916168213},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.13968494534492493},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/isbi.2012.6235610","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2012.6235610","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 9th IEEE International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},{"id":"pmid:24443675","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/24443675","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":"Proceedings. IEEE International Symposium on Biomedical Imaging","raw_type":null},{"id":"pmh:oai:europepmc.org:2878480","is_oa":false,"landing_page_url":"http://europepmc.org/articles/PMC3892901","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"pmh:oai:publications.polymtl.ca:15206","is_oa":false,"landing_page_url":"https://publications.polymtl.ca/15206/","pdf_url":null,"source":{"id":"https://openalex.org/S4306401013","display_name":"PolyPublie (\u00c9cole Polytechnique de Montr\u00e9al)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45683168","host_organization_name":"Polytechnique Montr\u00e9al","host_organization_lineage":["https://openalex.org/I45683168"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Communication de conf\u00e9rence"},{"id":"pmh:oai:pubmedcentral.nih.gov:3892901","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/3892901","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc IEEE Int Symp Biomed Imaging","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:3892901","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/3892901","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc IEEE Int Symp Biomed Imaging","raw_type":"Text"},"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.800000011920929,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1989102171","https://openalex.org/W2053186076","https://openalex.org/W2062243222","https://openalex.org/W2137744877","https://openalex.org/W2145714441","https://openalex.org/W2146980616","https://openalex.org/W2153119123","https://openalex.org/W2163082278","https://openalex.org/W6638695004","https://openalex.org/W6650119846"],"related_works":["https://openalex.org/W4321650139","https://openalex.org/W1999239650","https://openalex.org/W2169275958","https://openalex.org/W2506314341","https://openalex.org/W1557094818","https://openalex.org/W2917687159","https://openalex.org/W3204435187","https://openalex.org/W1969803895","https://openalex.org/W4235003028","https://openalex.org/W1986092654"],"abstract_inverted_index":{"Brain":[0],"abnormalities":[1],"such":[2],"as":[3,129],"white":[4],"matter":[5],"lesions":[6],"(WMLs)":[7],"are":[8,104],"not":[9],"only":[10],"linked":[11],"to":[12,56,89,181,203],"cerebrovascular":[13,28],"disease,":[14],"but":[15],"also":[16],"with":[17,172,186],"normal":[18],"aging,":[19],"diabetes":[20],"and":[21,49,54,126,157,166,193],"other":[22],"conditions":[23],"increasing":[24],"the":[25,35,68,76,97,102,115,122,138,176,183,194,197],"risk":[26],"for":[27,45,50,66,200],"pathologies.":[29],"Obtaining":[30],"quantitative":[31],"measures":[32],"which":[33],"assesses":[34],"degree":[36],"or":[37],"probability":[38],"of":[39,70,75,96,145,151,178,196],"WML":[40,165],"in":[41,72,93,114,137,154,169,191],"patients":[42],"is":[43],"important":[44],"evaluating":[46,51],"disease":[47],"burden,":[48],"its":[52],"progression":[53],"response":[55],"interventions.":[57],"In":[58],"this":[59],"paper,":[60],"we":[61],"introduce":[62],"a":[63,130,143,204],"novel":[64],"approach":[65],"detecting":[67],"presence":[69],"WMLs":[71],"periventricular":[73],"areas":[74,168],"brain":[77,98],"using":[78],"manifold-constrained":[79],"embeddings.":[80],"The":[81],"proposed":[82],"method":[83],"uses":[84],"locally":[85,111],"linear":[86,112],"embedding":[87],"(LLE)":[88],"create":[90,142],"\"normality\"":[91],"distributions":[92],"12":[94],"locations":[95],"where":[99],"deviations":[100],"from":[101,148],"manifolds":[103],"estimated":[105],"by":[106],"calculating":[107],"geodesic":[108],"distances":[109],"along":[110],"planes":[113],"embedding.":[116],"A":[117],"smooth":[118],"mapping":[119],"function":[120],"approximating":[121],"relationship":[123],"between":[124],"ambient":[125],"manifold":[127],"spaces":[128],"joint":[131],"distribution":[132],"maps":[133],"unseen":[134],"test":[135,158],"images":[136],"intrinsic":[139],"space.":[140],"We":[141],"set":[144],"low-dimensional":[146],"embeddings":[147],"876":[149],"patches":[150,162],"healthy":[152,167],"tissue":[153],"73":[155],"subjects":[156,171],"it":[159],"on":[160],"396":[161],"imaging":[163],"both":[164],"33":[170],"diabetes.":[173],"Experiments":[174],"highlight":[175],"need":[177],"nonlinear":[179],"techniques":[180],"learn":[182],"studied":[184],"data":[185],"detection":[187],"rates":[188],"over":[189],"85%":[190],"true-positives,":[192],"relevance":[195],"computed":[198],"distance":[199],"comparing":[201],"individuals":[202],"specific":[205],"pathological":[206],"pattern.":[207]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
