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dc.contributor.authorDing, T.
dc.contributor.authorCohen, A.D.
dc.contributor.authorO'Connor, E.E.
dc.date.accessioned2020-02-04T17:04:33Z
dc.date.available2020-02-04T17:04:33Z
dc.date.issued2020
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85077663515&doi=10.1016%2fj.nicl.2019.102151&partnerID=40&md5=b6a7d052443f0aad2e53a2d10924b979
dc.identifier.urihttp://hdl.handle.net/10713/11686
dc.description.abstractAutomated segmentation of the aging brain raises significant challenges because of the prevalence, extent, and heterogeneity of white matter hyperintensities. White matter hyperintensities can be frequently identified in magnetic resonance imaging (MRI) scans of older individuals and among those who have Alzheimer's disease. We propose OASIS-AD, a method for automatic segmentation of white matter hyperintensities in older adults using structural brain MRIs. OASIS-AD is an approach evolved from OASIS, which was developed for automatic lesion segmentation in multiple sclerosis. OASIS-AD is a major refinement of OASIS that takes into account the specific challenges raised by white matter hyperintensities in Alzheimer's disease. In particular, OASIS-AD combines three processing steps: 1) using an eroding procedure on the skull stripped mask; 2) adding a nearest neighbor feature construction approach; and 3) applying a Gaussian filter to refine segmentation results, creating a novel process for WMH detection in aging population. We show that OASIS-AD performs better than existing automatic white matter hyperintensity segmentation approaches. Copyright 2020 The Authorsen_US
dc.description.sponsorshipThis work was supported by the following National Institutes of Health /NIA grants: R01 AG063752 , P30 AG066468 , RF1 AG025516 , P01 AG025204 , R01 AG034852 , R01 GM113243 .en_US
dc.description.urihttps://doi.org/10.1016/j.nicl.2019.102151en_US
dc.language.isoen_USen_US
dc.publisherElsevier Inc.en_US
dc.relation.ispartofNeuroImage: Clinical
dc.subjectAlzheimer's diseaseen_US
dc.subjectBrainen_US
dc.subjectMRIen_US
dc.subjectOASISen_US
dc.subjectStatistical methods neuroimagingen_US
dc.subjectWMH segmentationen_US
dc.titleAn improved algorithm of white matter hyperintensity detection in elderly adultsen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.nicl.2019.102151


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