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An improved algorithm of white matter hyperintensity detection in elderly adults

Authors
  • Ding, T1
  • Cohen, AD1
  • O’Connor, EE2
  • Karim, HT1
  • Crainiceanu, A3
  • Muschelli, J4
  • Lopez, O1
  • Klunk, WE1
  • Aizenstein, HJ1
  • Krafty, R1
  • Crainiceanu, CM4
  • Tudorascu, DL1
  • 1 University of Pittsburgh, Pittsburgh
  • 2 University of Maryland, Baltimore
  • 3 United States Naval Academy, United States
  • 4 Johns Hopkins University, United States
Type
Published Article
Journal
NeuroImage Clinical
Publisher
Elsevier
Publication Date
Dec 27, 2019
Volume
25
Identifiers
DOI: 10.1016/j.nicl.2019.102151
PMID: 31927502
PMCID: PMC6957792
Source
PubMed Central
Keywords
License
Unknown

Abstract

Automated 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.

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