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Stochastic process for white matter injury detection in preterm neonates
NeuroImage: Clinical
  • Irene Cheng, University of Alberta
  • Steven P. Miller, Hospital for Sick Children University of Toronto
  • Emma G. Duerden, Hospital for Sick Children University of Toronto
  • Kaiyu Sun, University of Alberta
  • Vann Chau, Hospital for Sick Children University of Toronto
  • Elysia Adams, Hospital for Sick Children University of Toronto
  • Kenneth J. Poskitt, The University of British Columbia
  • Helen M. Branson, Hospital for Sick Children University of Toronto
  • Anup Basu, University of Alberta
Document Type
Article
Publication Date
2-26-2015
URL with Digital Object Identifier
10.1016/j.nicl.2015.02.015
Abstract

Preterm births are rising in Canada and worldwide. As clinicians strive to identify preterm neonates at greatest risk of significant developmental or motor problems, accurate predictive tools are required. Infants at highest risk will be able to receive early developmental interventions, and will also enable clinicians to implement and evaluate new methods to improve outcomes. While severe white matter injury (WMI) is associated with adverse developmental outcome, more subtle injuries are difficult to identify and the association with later impairments remains unknown. Thus, our goal was to develop an automated method for detection and visualization of brain abnormalities in MR images acquired in very preterm born neonates. We have developed a technique to detect WMI in T1-weighted images acquired in 177 very preterm born infants (24-32 weeks gestation). Our approach uses a stochastic process that estimates the likelihood of intensity variations in nearby pixels; with small variations being more likely than large variations. We first detect the boundaries between normal and injured regions of the white matter. Following this we use a measure of pixel similarity to identify WMI regions. Our algorithm is able to detect WMI in all of the images in the ground truth dataset with some false positives in situations where the white matter region is not segmented accurately.

Citation Information
Irene Cheng, Steven P. Miller, Emma G. Duerden, Kaiyu Sun, et al.. "Stochastic process for white matter injury detection in preterm neonates" NeuroImage: Clinical Vol. 7 (2015) p. 622 - 630
Available at: http://works.bepress.com/emma-duerden/24/