A quantitative analysis of small structures such as focal lesions in patients suffering from multiple sclerosis (MS) is an important issue in both diagnosis and therapy monitoring. In order to reach clinical relevance, the reproducibility and especially the accuracy of a proposed method has to be validated. We propose a framework for the generation of realistic digital phantoms of MS lesions of...

Parametric images can help investigate disease mechanisms and vital functions. To estimate parametric images, it is necessary to obtain the tissue time activity curves (tTACs), which express temporal changes of tracer activity in human tissue. In general, the tTACs are calculated from each voxel’s value of the time sequential PET images estimated from dynamic PET data. Recently, spatio-temporal...

Diffusion weighted magnetic resonance imaging is widely used to study the structure of the fiber pathways of brain white matter. We present our automatic reconstruction and tractography methods and the results obtained for the “Fiber Cup 2009” contest phantom. We fit the classic Diffusion Tensor which is a plausible model for voxels containing a single axon bundle and also the Diffusion Basis F...

In this study, a fast and clinically feasible residual-bootstrapping algorithm using a geometrically constrained two-tensor diffusion model is employed for estimating uncertainty in fibre orientation. Voxels are classified based on tensor morphologies before applying a single or two tensor residual-bootstrapping algorithms. Classification of tensor morphologies allows the tensor morphology to b...

In this paper, we present a fuzzy Markovian method for brain tissue segmentation from magnetic resonance images. Generally, there are three main brain tissues in a brain dataset: gray matter, white matter, and cerebrospinal fluid. However, due to the limited resolution of the acquisition system, many voxels may be composed of multiple tissue types (partial volume effects). The proposed method a...

In this paper we present an automatic statistical intensity basedapproach for extracting the 3D cerebrovascular system from time-of-flight (TOF) magnetic resonance angiography (MRA) data. The voxels of the dataset are classified as either background tissues, which are modeled by a finite mixture of one Rayleigh and two normal distributions, or blood vessels, which are modeled by one normal dist...

Introduction Echo planar spectroscopic imaging (EPSI) is one of several approaches to speeding up acquisitions of metabolite spectra from multiple voxels [1, 2]. However, EPSI measurements are very sensitive to temporally and spatially dependent phase and frequency shifts that arise from eddy current caused by oscillating readout gradient of the EPSI sequence. As a result, these phase and frequ...

We develop a differential geometric framework for regularizing diffusion MRI data. The key idea is to model white matter fibers as 3D space curves and to then extend Parent and Zucker's 2D curve inference approach [8] by using a notion of co-helicity to indicate compatibility between fibre orientation estimates at each voxel with those in a local neighborhood. We argue that this provides severa...

An overview of quasi-static electromagnetic dosimetry is presented. After an introductive description of quantities and standards and a quick look at experimental and analytical approaches, attention is focused on numerical dosimetry. The process that leads to the calculation of results is analyzed in its basic steps, including the representation of the human body by means of a realistic voxel ...