Simultaneous Smoothing and Estimation of the Tensor Field from Diffusion Tens or MRI
نویسندگان
چکیده
Diffusion tensor magnetic resonance imaging (DT-MRI) is a relatively new imaging modality in the field of medical imaging. This modality of imaging allows one to capture the structural connectivity if any between functionally meaningful regions for example, in the brain. The data however can be noisy and requires restoration. In this paper, we present a novel unified model for simultaneous smoothing and estimation of diffusion tensor field from DT-MRI. The diffusion tensor field is estimated directly from the raw data with smoothness and positive definiteness constraints. The data term we employ is from the original StejskalTanner equation instead of the linearized version as usually done in literature. In addition, we use Cholesky decomposition to ensure positive definiteness of the diffusion tensor. The unified model is discretized and solved numerically using limited memory Quasi-Newton method. Both synthetic and real data experiments are shown to depict the algorithm performance.
منابع مشابه
Simultaneous Smoothing & Estimation of DTI via Robust Variational Non-local Means
Regularized diffusion tensor estimation is an essential step in DTI analysis. There are many methods proposed in literature for this task but most of them are neither statistically robust nor feature preserving denoising techniques that can simultaneously estimate symmetric positive definite (SPD) diffusion tensors from diffusion MRI. One of the most popular techniques in recent times for featu...
متن کاملA robust variational approach for simultaneous smoothing and estimation of DTI
Estimating diffusion tensors is an essential step in many applications - such as diffusion tensor image (DTI) registration, segmentation and fiber tractography. Most of the methods proposed in the literature for this task are not simultaneously statistically robust and feature preserving techniques. In this paper, we propose a novel and robust variational framework for simultaneous smoothing an...
متن کاملA Constrained Variational Principle for Direct Estimation and Smoothing of the Diffusion Tensor Field from DWI
In this paper, we present a novel constrained variational principle for simultaneous smoothing and estimation of the diffusion tensor field from diffusion weighted imaging (DWI). The constrained variational principle involves the minimization of a regularization term in an LP norm, subject to a nonlinear inequality constraint on the data. The data term we employ is the original Stejskal-Tanner ...
متن کاملDetermination of Fiber Direction in High Angular Resolution Diffusion Images using Spherical Harmonics Functions and Wiener Filter
Diffusion tensor imaging (DTI) MRI is a noninvasive imaging method of the cerebral tissues whose fibers directions are not evaluated correctly in the regions of the crossing fibers. For the same reason the high angular resolution diffusion images (HARDI) are used for estimation of the fiber direction in each voxel. One of the main methods to specify the direction of fibers is usage of the spher...
متن کاملEvaluation of the relationship between axon injury and clinical symptoms in patients with multiple sclerosis using diffusion tensor MRI imaging
Background: Magnetic resonance imaging (MRI) is a non-invasive imaging technology that shows detailed anatomical and pathological images. It is often used for disease detection, diagnosis, and treatment monitoring, in particular with neurodegenerative diseases, such as Multiple sclerosis (MS), Alzheimer's and amyotrophic lateral sclerosis. However, conventional MRI provides only qualitative inf...
متن کامل