Comparing isotropic and anisotropic smoothing for voxel-based DTI analyses: A simulation study.
نویسندگان
چکیده
Voxel-based analysis (VBA) methods are increasingly being used to compare diffusion tensor image (DTI) properties across different populations of subjects. Although VBA has many advantages, its results are highly dependent on several parameter settings, such as those from the coregistration technique applied to align the data, the smoothing kernel, the statistics, and the post-hoc analyses. In particular, to increase the signal-to-noise ratio and to mitigate the adverse effect of residual image misalignments, DTI data are often smoothed before VBA with an isotropic Gaussian kernel with a full width half maximum up to 16 x 16 x 16 mm(3). However, using isotropic smoothing kernels can significantly partial volume or voxel averaging artifacts, adversely affecting the true diffusion properties of the underlying fiber tissue. In this work, we compared VBA results between the isotropic and an anisotropic Gaussian filtering method using a simulated framework. Our results clearly demonstrate an increased sensitivity and specificity of detecting a predefined simulated pathology when the anisotropic smoothing kernel was used.
منابع مشابه
How to smooth diffusion tensor images in a voxel based analysis?
Introduction: Many DTI studies are starting to use voxel based analysis (VBA) to evaluate differences in the diffusion properties between healthy diseased subjects. Despite the intuitively appealing approach of analyzing diffusion measures at each voxel, VBA results should be interpreted cautiously, since they depend on the applied parameter settings. Since, for example, in the VBA literature o...
متن کاملDti in the Clinic: Evaluating the Effects of Smoothing
The accuracy and interpretation of results obtained by Diffusion Tensor Imaging (DTI) are largely influenced by several experimental parameter settings. In Voxel-Based (VB) analysis images are smoothed, in order to improve their Signal to Noise Ratio (SNR) and to reduce the impact of normalization and artifacts. This is a critical step and care must be taken so that directional information and ...
متن کاملSpatial Smoothing for Diffusion Tensor Imaging with low Signal to Noise Ratios
Though low signal to noise ratio (SNR) experiments in DTI give key information about tracking and anisotropy, e.g. by measurements with very small voxel sizes, due to the complicated impact of thermal noise such experiments are up to now seldom analysed. In this paper Monte Carlo simulations are presented which investigate the random fields of noise for different DTI variables in low SNR situat...
متن کاملAnisotropic Kernel Smoothing of DTI Data
J. E. Lee, M. K. Chung, T. R. Oakes, A. L. Alexander Medical Physics, University of Wisconsin, Madison, WI, United States, The Waisman Laboratory for Functional Brain Imaging and Behavior, University of Wisconsin, Madison, WI, United States, Statistics, University of Wisconsin, Madison, WI, United States Introduction DTI measures, such as FA, trace and the eigenvector orientations, are very sen...
متن کاملA multi-structural Fiber Crossing Anisotropic Diffusion Phantom for HARDI reconstruction techniques validation
Introduction There is significant interest in evaluating the performance and reliability of white matter fiber tractography algorithms. Diffusion tensor imaging (DTI) approach [1] is a powerful tool for non-invasive investigation of microstructure and has been successfully applied to detect different white matter diseases [2]. DTI-based fiber tracking gives insights into the complex architectur...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Human brain mapping
دوره 31 1 شماره
صفحات -
تاریخ انتشار 2010