Advanced diffusion imaging enables the reconstruction of complex fiber configurations such as crossings or fannings. However, resulting visualizations often suffer from visual clutter which makes exploration challenging. This paper presents the BundleExplorer as a GPU-based focus and context rendering framework for diffusion data. A combination of a fiber encompassing hull and line rendering is...

Diffusion tensor imaging (DTI) is a sensitive tool for the assessment of microstructural alterations in brain white matter (WM). We propose a new processing technique to detect, local and global longitudinal changes of diffusivity metrics, in homologous regions along WM fiber-bundles. To this end, a reliable and automatic processing pipeline was developed in three steps: 1) co-registration and ...

Given a fiber bundle of GKM spaces, π : M → B, we analyze the structure of the equivariant K-ring of M as a module over the equivariant K-ring of B by translating the fiber bundle, π, into a fiber bundle of GKM graphs and constructing, by combinatorial techniques, a basis of this module consisting of K-classes which are invariant under the natural holonomy action on the K-ring of M of the funda...

The fiber bundle model is one of the most important theoretical approaches to investigate the fracture and breakdown of disordered media extensively used both by the engineering and physics community. We present the basic construction of the model and provide a brief overview of recent results focusing mainly on the physics literature. We discuss the limitations of the model to describe the fai...

We introduce a continuous damage fiber bundle model and compare its behavior with that of dry fiber bundles. Several interesting constitutive behaviors, such as plasticity, are found in this model depending on the value of the damage parameter and on the form of the disorder distribution. We compare the constitutive behavior of global load transfer models, obtained analytically, with local load...

Reliable quantitative analysis of white matter connectivity in the brain is an open problem in neuroimaging, with common solutions requiring tools for fiber tracking, tractography segmentation and estimation of intersubject correspondence. This paper proposes a novel, template matching approach to the problem. In the proposed method, a deformable fiber-bundle model is aligned directly with the ...

Multi-diameter single fiber reflectance (MDSFR) spectroscopy enables quantitative measurement of tissue optical properties, including the reduced scattering coefficient and the phase function parameter γ. However, the accuracy and speed of the procedure are currently limited by the need for co-localized measurements using multiple fiber optic probes with different fiber diameters. This study de...

Given a holomorphic vector bundle F over a compact Riemann surface X, and a subspace Sx ⊂ Fx in the fiber over a point x, the Hecke transformation produces a new vector bundle E on X [10, 16]. The vector bundle E is the kernel of the natural quotient map F −→ Fx/Sx. Hecke transformation is a very useful tool to study the moduli space. For instance, they are used in computation of cohomologies o...

Compressive sensing (CS) has proven to be a viable method for reconstructing high-resolution signals using lowresolution measurements. Integrating CS principles into an optical system allows for higher-resolution imaging using lower-resolution sensor arrays. In contrast to prior works on CS-based imaging, our focus in this paper is on imaging through fiber-optic bundles, in which manufacturing ...