A scale-space aproach to nonlocal optical flow calculations

[EN] This paper presents an interpretation of a classic optical flow method by Nagel and Enkelmann as a tensor-driven anisotropic diffusion approach in digital image analysis. We introduce an improvement into the model formulation, and we establish well-posedness results for the resulting system of parabolic partial differential equations. Our method avoids linearizations in the optical flow constraint, and it can recover displacement fields which are far beyond the typical one-pixel limits that are characteristic for many differential methods for optical flow recovery. A robust numerical scheme is presented in detail. We avoid convergence to irrelevant local minima by embedding our method into a linear scale-space framework and using a focusing strategy from coarse to fine scales. The high accuracy of the proposed method is demonstrated by means of a synthetic and a real-world image sequence.

Regularization of 3D cylindrical surfaces

[EN] In this paper we present a method for the regularization of 3D cylindrical surfaces. By a cylindrical surface we mean a 3D surface that can be expressed as an application S(l; µ) ! R3 , where (l; µ) represents a cylindrical parametrization of the 3D surface. We built an initial cylindrical parametrization of the surface. We propose a new method to regularize such cylindrical surface. This method takes into account the information supplied by the disparity maps computed between pair of images to constraint the regularization of the set of 3D points. We propose a model based on an energy which is composed of two terms: an attachment term that minimizes the difference between the image coordinates and the disparity maps and a second term that enables a regularization by means of anisotropic diffusion. One interesting advantage of this approach is that we regularize the 3D surface by using a bi-dimensional minimization problem.

Microstructure and Cerebral Blood Flow within White Matter of the Human Brain: A TBSS Analysis.

BACKGROUND White matter (WM) fibers connect different brain regions and are critical for proper brain function. However, little is known about the cerebral blood flow in WM and its relation to WM microstructure. Recent improvements in measuring cerebral blood flow (CBF) by means of arterial spin labeling (ASL) suggest that the signal in white matter may be detected. Its implications for physiology needs to be extensively explored. For this purpose, CBF and its relation to anisotropic diffusion was analyzed across subjects on a voxel-wise basis with tract-based spatial statistics (TBSS) and also across white matter tracts within subjects. METHODS Diffusion tensor imaging and ASL were acquired in 43 healthy subjects (mean age = 26.3 years). RESULTS CBF in WM was observed to correlate positively with fractional anisotropy across subjects in parts of the splenium of corpus callosum, the right posterior thalamic radiation (including the optic radiation), the forceps major, the right inferior fronto-occipital fasciculus, the right inferior longitudinal fasciculus and the right superior longitudinal fasciculus. Furthermore, radial diffusivity correlated negatively with CBF across subjects in similar regions. Moreover, CBF and FA correlated positively across white matter tracts within subjects. CONCLUSION The currently observed findings on a macroscopic level might reflect the metabolic demand of white matter on a microscopic level involving myelination processes or axonal function. However, the exact underlying physiological mechanism of this relationship needs further evaluation.

Desarrollo de métodos de procesado de imágenes laríngeas en color para la detección del espacio glotal y de las cuerdas vocales

La medicina ha evolucionado de forma que las imágenes digitales tienen un papel de gran relevancia para llevar a cabo el diagnóstico de enfermedades. Son muchos y de diversa naturaleza los problemas que pueden presentar el aparato fonador. Un paso previo para la caracterización de imágenes digitales de la laringe es la segmentación de las cuerdas vocales. Hasta el momento se han desarrollado algoritmos que permiten la segmentación de la glotis. El presente proyecto pretende avanzar un paso más en el estudio, procurando asimismo la segmentación de las cuerdas vocales. Para ello, es necesario aprovechar la información de color que ofrecen las imágenes, pues es lo que va a determinar la diferencia entre una región y otra de la imagen. En este proyecto se ha desarrollado un novedoso método de segmentación de imágenes en color estroboscópicas de la laringe basado en el crecimiento de regiones a partir de píxeles-semilla. Debido a los problemas que presentan las imágenes obtenidas por la técnica de la estroboscopia, para conseguir óptimos resultados de la segmentación es necesario someter a las imágenes a un preprocesado, que consiste en la eliminación de altos brillos y aplicación de un filtro de difusión anisotrópica. Tras el preprocesado, comienza el crecimiento de la región a partir de unas semillas que se obtienen previamente. La condición de inclusión de un píxel en la región se basa en un parámetro de tolerancia que se determina de forma adaptativa. Este parámetro comienza teniendo un valor muy bajo y va aumentando de forma recursiva hasta alcanzar una condición de parada. Esta condición se basa en el análisis de la distribución estadística de los píxeles dentro de la región que va creciendo. La última fase del proyecto consiste en la realización de las pruebas necesarias para verificar el funcionamiento del sistema diseñado, obteniéndose buenos resultados en la segmentación de la glotis y resultados esperanzadores para seguir mejorando el sistema para la segmentación de las cuerdas vocales. ABSTRACT Medicine has evolved so that digital images have a very important role to perform disease diagnosis. There are wide variety of problems that can present the vocal apparatus. A preliminary step for characterization of digital images of the larynx is the segmentation of the vocal folds. To date, some algorithms that allow the segmentation of the glottis have been developed. This project aims to go one step further in the study, also seeking the segmentation of the vocal folds. To do this, we must use the color information offered by images, since this is what will determine the difference between different regions in a picture. In this project a novel method of larynx color images segmentation based on region growing from a pixel seed is developed. Due to the problems of the images obtained by the technique of stroboscopy, to achieve optimal results of the segmentation is necessary a preprocessing of the images, which involves the removal of high brightness and applying an anisotropic diffusion filter. After this preprocessing, the growth of the region from previously obtained seeds starts. The condition for inclusion of a pixel in the region is based on a tolerance parameter, which is adaptively determined. It initially has a low value and this is recursively increased until a stop condition is reached. This condition is based on the analysis of the statistical distribution of the pixels within the grown region. The last phase of the project involves the necessary tests to verify the proper working of the designed system, obtaining very good results in the segmentation of the glottis and encouraging results to keep improving the system for the segmentation of the vocal folds.

A second order control-volume finite-element least-squares strategy for simulating diffusion in strongly anisotropic media

An unstructured mesh �nite volume discretisation method for simulating di�usion in anisotropic media in two-dimensional space is discussed. This technique is considered as an extension of the fully implicit hybrid control-volume �nite-element method and it retains the local continuity of the ux at the control volume faces. A least squares function recon- struction technique together with a new ux decomposition strategy is used to obtain an accurate ux approximation at the control volume face, ensuring that the overall accuracy of the spatial discretisation maintains second order. This paper highlights that the new technique coincides with the traditional shape function technique when the correction term is neglected and that it signi�cantly increases the accuracy of the previous linear scheme on coarse meshes when applied to media that exhibit very strong to extreme anisotropy ratios. It is concluded that the method can be used on both regular and irregular meshes, and appears independent of the mesh quality.

Molecular dynamics-based approach to study the anisotropic self-diffusion of molecules in porous materials with multiple cage types: Application to H-2 in losod

Van den Berg, A. W. C., Flikkema, E., Lems, S., Bromley, S. T., Jansen, J. C. (2006). Molecular dynamics-based approach to study the anisotropic self-diffusion of molecules in porous materials with multiple cage types: Application to H-2 in losod. Journal of physical chemistry b, 110 (1), 501-506. RAE2008

Diffusion tensor of water in model articular cartilage

We used Monte Carlo simulations of Brownian dynamics of water to study anisotropic water diffusion in an idealised model of articular cartilage. The main aim was to use the simulations as a tool for translation of the fractional anisotropy of the water diffusion tensor in cartilage into quantitative characteristics of its collagen fibre network. The key finding was a linear empirical relationship between the collagen volume fraction and the fractional anisotropy of the diffusion tensor. Fractional anisotropy of the diffusion tensor is potentially a robust indicator of the microstructure of the tissue because, in the first approximation, it is invariant to the inclusion of proteoglycans or chemical exchange between free and collagen-bound water in the model. We discuss potential applications of Monte Carlo diffusion-tensor simulations for quantitative biophysical interpretation of MRI diffusion-tensor images of cartilage. Extension of the model to include collagen fibre disorder is also discussed.

Computer modeling of diffusion in biological tissues

Molecular-level computer simulations of restricted water diffusion can be used to develop models for relating diffusion tensor imaging measurements of anisotropic tissue to microstructural tissue characteristics. The diffusion tensors resulting from these simulations can then be analyzed in terms of their relationship to the structural anisotropy of the model used. As the translational motion of water molecules is essentially random, their dynamics can be effectively simulated using computers. In addition to modeling water dynamics and water-tissue interactions, the simulation software of the present study was developed to automatically generate collagen fiber networks from user-defined parameters. This flexibility provides the opportunity for further investigations of the relationship between the diffusion tensor of water and morphologically different models representing different anisotropic tissues.

Characterisation of the micro-architecture of direct writing melt electrospun tissue engineering scaffolds using diffusion tensor and computed tomography microimaging

This article describes the first steps toward comprehensive characterization of molecular transport within scaffolds for tissue engineering. The scaffolds were fabricated using a novel melt electrospinning technique capable of constructing 3D lattices of layered polymer fibers with well - defined internal microarchitectures. The general morphology and structure order was then determined using T 2 - weighted magnetic resonance imaging and X - ray microcomputed tomography. Diffusion tensor microimaging was used to measure the time - dependent diffusivity and diffusion anisotropy within the scaffolds. The measured diffusion tensors were anisotropic and consistent with the cross - hatched geometry of the scaffolds: diffusion was least restricted in the direction perpendicular to the fiber layers. The results demonstrate that the cross - hatched scaffold structure preferentially promotes molecular transport vertically through the layers ( z - axis), with more restricted diffusion in the directions of the fiber layers ( x – y plane). Diffusivity in the x – y plane was observed to be invariant to the fiber thickness. The characteristic pore size of the fiber scaffolds can be probed by sampling the diffusion tensor at multiple diffusion times. Prospective application of diffusion tensor imaging for the real - time monitoring of tissue maturation and nutrient transport pathways within tissue engineering scaffolds is discussed.

Brain fiber architecture, genetics, and intelligence: a high angular resolution diffusion imaging (HARDI) study

We developed an analysis pipeline enabling population studies of HARDI data, and applied it to map genetic influences on fiber architecture in 90 twin subjects. We applied tensor-driven 3D fluid registration to HARDI, resampling the spherical fiber orientation distribution functions (ODFs) in appropriate Riemannian manifolds, after ODF regularization and sharpening. Fitting structural equation models (SEM) from quantitative genetics, we evaluated genetic influences on the Jensen-Shannon divergence (JSD), a novel measure of fiber spatial coherence, and on the generalized fiber anisotropy (GFA) a measure of fiber integrity. With random-effects regression, we mapped regions where diffusion profiles were highly correlated with subjects' intelligence quotient (IQ). Fiber complexity was predominantly under genetic control, and higher in more highly anisotropic regions; the proportion of genetic versus environmental control varied spatially. Our methods show promise for discovering genes affecting fiber connectivity in the brain.

Mapping genetic influences on brain fiber architecture with high angular resolution diffusion imaging (HARDI)

We report the first 3D maps of genetic effects on brain fiber complexity. We analyzed HARDI brain imaging data from 90 young adult twins using an information-theoretic measure, the Jensen-Shannon divergence (JSD), to gauge the regional complexity of the white matter fiber orientation distribution functions (ODF). HARDI data were fluidly registered using Karcher means and ODF square-roots for interpol ation; each subject's JSD map was computed from the spatial coherence of the ODFs in each voxel's neighborhood. We evaluated the genetic influences on generalized fiber anisotropy (GFA) and complexity (JSD) using structural equation models (SEM). At each voxel, genetic and environmental components of data variation were estimated, and their goodness of fit tested by permutation. Color-coded maps revealed that the optimal models varied for different brain regions. Fiber complexity was predominantly under genetic control, and was higher in more highly anisotropic regions. These methods show promise for discovering factors affecting fiber connectivity in the brain.

Bioconvection in an anisotropic scattering suspension of phototactic algae

Phototaxis is a directed swimming response dependent upon the light intensity sensed by microorganisms. Positive phototaxis denotes motion directed towards the source of light and negative phototaxis is motion directed away from it. In this paper, we investigate the onset of bioconvection in a suspension of anisotropic scattering phototactic algae illuminated by collimated radiation at the top. The basic state of the system is defined by the zero fluid flow and the up and down swimming, caused by the positive and negative phototaxis, is balanced by the diffusion. A comprehensive numerical study of the linear stability is presented with particular emphasis on the forward scattering effect. The onset of bioconvection occurs either via a stationary mode or an oscillatory mode. The transition from a stationary mode to an oscillatory mode or vice versa has been observed as the anisotropic coefficient is varied for certain parameter values. (C) 2012 Elsevier Masson SAS. All rights reserved.

Vesicular Nanostructure Formation by Self-Assembly of Anisotropic Penta-phenol-Substituted Fullerene in Water

A study on self-assembly of anisotropically substituted penta-aryl fullerenes in water has been reported. The penta-phenol-substituted amphiphilic fullerene derivative C60Ph5(OH)(5)],exhibited self-assembled vesicular nanostructures in water under the experimental conditions. The size of the vesicles Was observed to depend upon the kinetics of self-assembly and could be varied from similar to 300 to similar to 70 nm. Our mechanistic study indicated that the self-assembly of C60Ph5(OH)(5) is driven by extensive intermolecular as well as water-mediated hydrogen :bonding along with fullerene-fullerene hydrophobic interaction in water. The cumulative effect of these interactions is responsible for the stability of vesicular structures even on the removal of solvent. The substitution of phenol with anisole resulted in different packing and interaction of the fullerene derivative, as Indicated in the molecular dynamics studies, thus resulting in different self-assembled nanostructures. The hollow vesicles were further encapsulated with a hydrophobic conjugated polymer and water-soluble dye as guest molecules. Such confinement of pi-conjugated polymers in fullerene has significance in bulk heterojunction devices for efficient exciton diffusion.

Between scylla and charybdis: Hydrophobic graphene-guided water diffusion on hydrophilic substrates

The structure of water confined in nanometer-sized cavities is important because, at this scale, a large fraction of hydrogen bonds can be perturbed by interaction with the confining walls. Unusual fluidity properties can thus be expected in the narrow pores, leading to new phenomena like the enhanced fluidity reported in carbon nanotubes. Crystalline mica and amorphous silicon dioxide are hydrophilic substrates that strongly adsorb water. Graphene, on the other hand, interacts weakly with water. This presents the question as to what determines the structure and diffusivity of water when intercalated between hydrophilic substrates and hydrophobic graphene. Using atomic force microscopy, we have found that while the hydrophilic substrates determine the structure of water near its surface, graphene guides its diffusion, favouring growth of intercalated water domains along the C-C bond zigzag direction. Molecular dynamics and density functional calculations are provided to help understand the highly anisotropic water stripe patterns observed.