Quantitative analysis of human brain MR images at ultrahigh field strength

Leiden Repository

Quantitative analysis of human brain MR images at ultrahigh field strength

Title: Quantitative analysis of human brain MR images at ultrahigh field strength
Author: Doan, Nhat Trung
Publisher: Department of Radiology, Faculty of Medicine / Leiden University Medical Center (LUMC), Leiden University
Issue Date: 2014-06-17
Keywords: Texture analysis
Segmentation
MR phase
Ultrahigh field
Susceptibility
Brain structures
Abstract: T2*-weighted imaging provides a non-invasive means to study susceptibility changes of substances such as myelin and iron in the brain. Particularly, phase images show an increased sensitivity to magnetic susceptibility differences with increased field strengths. The primary goal of the thesis was to develop methods for quantitative analysis of human brain T2*-weighted images at ultrahigh field strength. Additionally, it was also aimed to investigate the use of textural features derived from whole-brain deformation field for classification of Alzheimer’s disease (AD). A framework for the detection of between-group textural differences in 7T T2*-weighted magnitude and phase images of subcortical structures was presented, and its application was demonstrated in Huntington’s disease. A novel algorithm for segmentation of the cerebral cortex from 7T T2*-weighted images was proposed and extensively validated. Subsequently, a highly automated method was proposed for quantification of regional changes in these images in terms of gray matter/white matter contrast and cortical profile. In addition to an analysis of aging effect using data of young and elderly healthy subjects, this method was also applied to compare early- and late- onset AD patients. The analysis techniques presented in this thesis can be useful tools for susceptibility studies using ultrahigh field MR images
Description: Promotores: B.P.F. Lelieveldt, M.A. van Buchem, Co-promotor: J.R. Milles
With summary in Dutch
Faculty: LUMC
Citation: Doan, N.T., 2014, Doctoral thesis, Leiden University
ISBN: 9789053358702
Handle: http://hdl.handle.net/1887/26921
 

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