Ultrasound imaging is an incontestable vital tool for diagnosis, it provides in non-invasive manner the internal structure of the body to detect eventually diseases or abnormalities tissues. Unfortunately, the presence of speckle noise in these images affects edges and fine details which limit the contrast resolution and make diagnostic more difficult. In this paper, we propose a denoising appr...

Riemannian geometry has become a popular mathematical framework for the analysis of diffusion tensor images (DTI) in diffusion weighted magnetic resonance imaging (DWMRI). If one declines from the a priori constraint to model local anisotropic diffusion in terms of a 6-degrees-of-freedom rank-2 DTI tensor, then Riemann-Finsler geometry appears to be the natural extension. As such it provides an...

The presence of Rician noise in magnetic resonance imaging (MRI) introduces systematic errors in diffusion tensor imaging (DTI) measurements. This paper evaluates gradient direction schemes and tensor estimation routines to determine how to achieve the maximum accuracy and precision of tensor derived measures for a fixed amount of scan time. We present Monte Carlo simulations that quantify the ...

introduction: there is many ways to assessing the electrical conductivity anisotropy of a tumor. applying the values of tissue electrical conductivity anisotropy is crucial in numerical modeling of the electric and thermal field distribution in electroporation treatments. this study aims to calculate the tissues electrical conductivity anisotropy in patients with sarcoma tumors using diffusion ...

Tractography algorithms for diffusion tensor (DT) images consecutively connect directions of maximal diffusion across neighboring DTs in order to reconstruct the 3-dimensional trajectories of white matter tracts in vivo in the human brain. The performance of these algorithms, however, is strongly influenced by the amount of noise in the images and by the presence of degenerate tensors-- i.e., t...

Roussos and Maragos proposed a method for image interpolation in “Reversible interpolation of vectorial images by an anisotropic diffusion-projection PDE.” An earlier version was also published in conference paper (Roussos and Maragos, “Vector-Valued Image Interpolation by an Anisotropic Diffusion-Projection PDE,” 2007). Given a discretely sampled image v, the method finds an image u such that ...

Tractography algorithms for diffusion tensor (DT) images consecutively connect directions of maximal diffusion across neighboring DTs in order to reconstruct the 3-dimensional trajectories of white matter tracts in vivo in the human brain. The performance of these algorithms, however, is strongly influenced by the amount of noise in the images and by the presence of degenerate tensors — i.e., t...

PURPOSE To prospectively evaluate several diffusion-tensor magnetic resonance (MR) imaging indexes (mean diffusivity [MD], fractional anisotropy [FA], and eigenvalues) of corticospinal tract impairment in patients with progressive muscular atrophy (PMA) and patients with amyotrophic lateral sclerosis (ALS). MATERIALS AND METHODS This study had institutional review board approval, and written ...

OBJECTIVES To investigate the extent of tissue damage in a region of normal appearing corpus callosum (NACC) for different forms of multiple sclerosis (MS) using diffusion tensor and proton magnetic resonance (MR) spectroscopic imaging. METHODS A total of 47 patients with MS and 15 controls were included. Regions of interest from the NACC were manually segmented using high resolution anatomic...

We address three crucial issues encountered in DT-MRI (Diffusion Tensor Magnetic Resonance Imaging) : diffusion tensor Estimation, Regularization and fiber bundle Visualization. We first review related algorithms existing in the literature and propose then alternative variational formalisms that lead to new and improved schemes, thanks to the preservation of important tensor constraints (positi...