Assessing intensity of white matter hyperintensity and normal appearing white matter in healthy adults

There have been interest on white matter hyperintensity (WMH) and normal white matter (WM) changes reported but have not yet been fully characterized. Different image sequences of magnetic resonance imaging (MRI) scans may shows different gray scale intensity. However, it is difficult to differentia...

Full description

Bibliographic Details
Published in:IECBES 2016 - IEEE-EMBS Conference on Biomedical Engineering and Sciences
Main Author: 2-s2.0-85015708870
Format: Conference paper
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2016
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015708870&doi=10.1109%2fIECBES.2016.7843502&partnerID=40&md5=f433c0289865f37b29559b9b72ce6ec1
Description
Summary:There have been interest on white matter hyperintensity (WMH) and normal white matter (WM) changes reported but have not yet been fully characterized. Different image sequences of magnetic resonance imaging (MRI) scans may shows different gray scale intensity. However, it is difficult to differentiate the intensity of normal WM and WMH as their intensities are visually not much different. In this study, normal WM and WMH changes were investigated based on their intensity to determine the correlation of WMH types and severity in brain of healthy subjects. The assessment was performed by using fully automatic WMH detection and computing algorithms. The main brain regions were segregated into gray matter (GM), normal WM, cerebrospinal fluid (CSF) and non-brain tissue. From the results, it shows that there was significant difference seen between normal appearing WM and hyperintense WM in terms of their intensity levels. The study shows that the development of WMH is prevalent to the occasion of normal WM changes. This is shows that WMH intensity reflects the level of WMH classes and severity; however, further investigations are needed to improve their efficiency. © 2016 IEEE.
ISSN:
DOI:10.1109/IECBES.2016.7843502