Bilateral loss of vestibular function: clinical findings in 53 patients

The clinical presentations and aetiologies of a series of 53 cases of bilateral vestibular failure (BVF) seen by the authors over a decade were evaluated by retrospective review of the medical records. Thirty-nine per cent of patients had associated neurological disease; 13% had a progressive cerebellar syndrome with disabling gait ataxia, abnormal eye movements and cerebellar atrophy on neuro-imaging. BVF was usually unsuspected. Nine per cent had cranial or peripheral neuropathies and in this group there was no abnormality of brain stem/cerebellar oculomotor function, but hearing loss was common. Eleven per cent revealed BVF and hearing loss secondary to meningitis, and 6% had other neurological disorders. Idiopathic BVF was found in 21% of cases, characterised by paroxysmal vertigo and/or oscillopsia, but no abnormal clinical signs. Gentamicin ototoxicity accounted for a further 17%, while autoimmune disease was present in 9% of patients. Otological or neoplastic disease was diagnosed in the remaining 13% of patients. It was concluded that neurological, audiological and ocular motor assessments allow the probable cause of BVF to be defined in approximately 80% of cases. A group of BVF related to autoimmune pathologies is reported for the first time, indicating the need for immunological screening. Idiopathic BVF may present with only minor visual or vestibular symptoms, while in patients with cerebellar degeneration, BVF may be unsuspected and, thus, underdiagnosed.     

Equi-affine Invariant Geometry for Shape Analysis

Traditional models of bendable surfaces are based on the exact or approximate invariance to deformations that do not tear or stretch the shape, leaving intact an intrinsic geometry associated with it. These geometries are typically defined using either the shortest path length (geodesic distance), or properties of heat diffusion (diffusion distance) on the surface. Both measures are implicitly derived from the metric induced by the ambient Euclidean space. In this paper, we depart from this restrictive assumption by observing that a different choice of the metric results in a richer set of geometric invariants. We apply equi-affine geometry for analyzing arbitrary shapes with positive Gaussian curvature. The potential of the proposed framework is explored in a range of applications such as shape matching and retrieval, symmetry detection, and computation of Voroni tessellation. We show that in some shape analysis tasks, equi-affine-invariant intrinsic geometries often outperform their Euclidean-based counterparts. We further explore the potential of this metric in facial anthropometry of newborns. We show that intrinsic properties of this homogeneous group are better captured using the equi-affine metric.     

Laplacian colormaps: a framework for structure‐preserving color transformations

Mappings between color spaces are ubiquitous in image processing problems such as gamut mapping, decolorization, and image optimization for color‐blind people. Simple color transformations often result in information loss and ambiguities, and one wishes to find an image‐specific transformation that would preserve as much as possible the structure of the original image in the target color space. In this paper, we propose Laplacian colormaps, a generic framework for structure‐preserving color transformations between images. We use the image Laplacian to capture the structural information, and show that if the color transformation between two images preserves the structure, the respective Laplacians have similar eigenvectors, or in other words, are approximately jointly diagonalizable. Employing the relation between joint diagonalizability and commutativity of matrices, we use Laplacians commutativity as a criterion of color mapping quality and minimize it w.r.t. the parameters of a color transformation to achieve optimal structure preservation. We show numerous applications of our approach, including color‐to‐gray conversion, gamut mapping, multispectral image fusion, and image optimization for color deficient viewers.     

Analysis of Two-Dimensional Non-Rigid Shapes

Analysis of deformable two-dimensional shapes is an important problem, encountered in numerous pattern recognition, computer vision and computer graphics applications. In this paper, we address three major problems in the analysis of non-rigid shapes: similarity, partial similarity, and correspondence. We present an axiomatic construction of similarity criteria for deformation-invariant shape comparison, based on intrinsic geometric properties of the shapes, and show that such criteria are related to the Gromov-Hausdorff distance. Next, we extend the problem of similarity computation to shapes which have similar parts but are dissimilar when considered as a whole, and present a construction of set-valued distances, based on the notion of Pareto optimality. Finally, we show that the correspondence between non-rigid shapes can be obtained as a byproduct of the non-rigid similarity problem. As a numerical framework, we use the generalized multidimensional scaling (GMDS) method, which is the numerical core of the three problems addressed in this paper.     

Topology-Invariant Similarity of Nonrigid Shapes

This paper explores the problem of similarity criteria between nonrigid shapes. Broadly speaking, such criteria are divided into intrinsic and extrinsic, the first referring to the metric structure of the object and the latter to how it is laid out in the Euclidean space. Both criteria have their advantages and disadvantages: extrinsic similarity is sensitive to nonrigid deformations, while intrinsic similarity is sensitive to topological noise. In this paper, we approach the problem from the perspective of metric geometry. We show that by unifying the extrinsic and intrinsic similarity criteria, it is possible to obtain a stronger topology-invariant similarity, suitable for comparing deformed shapes with different topology. We construct this new joint criterion as a tradeoff between the extrinsic and intrinsic similarity and use it as a set-valued distance. Numerical results demonstrate the efficiency of our approach in cases where using either extrinsic or intrinsic criteria alone would fail.     

Non‐Rigid Puzzles

Shape correspondence is a fundamental problem in computer graphics and vision, with applications in various problems including animation, texture mapping, robotic vision, medical imaging, archaeology and many more. In settings where the shapes are allowed to undergo non‐rigid deformations and only partial views are available, the problem becomes very challenging. To this end, we present a non‐rigid multi‐part shape matching algorithm. We assume to be given a reference shape and its multiple parts undergoing a non‐rigid deformation. Each of these query parts can be additionally contaminated by clutter, may overlap with other parts, and there might be missing parts or redundant ones. Our method simultaneously solves for the segmentation of the reference model, and for a dense correspondence to (subsets of) the parts. Experimental results on synthetic as well as real scans demonstrate the effectiveness of our method in dealing with this challenging matching scenario.     

On Solutions of Linear Ordinary Difference Equations in their Coefficient Field

We extend the notion of monomial extensions of differential fields, i.e. simple transcendental extensions in which the polynomials are closed under differentiation, to difference fields. The structure of such extensions provides an algebraic framework for solving generalized linear difference equations with coefficients in such fields. We then describe algorithms for finding the denominator of any solution of those equations in an important subclass of monomial extensions that includes transcendental indefinite sums and products. This reduces the general problem of finding the solutions of such equations in their coefficient fields to bounding their degrees. In the base case, this yields in particular a new algorithm for computing the rational solutions of q -difference equations with polynomial coefficients.     

Recent Trends,Applications, and Perspectives in 3D Shape Similarity Assessment

The recent introduction of 3D shape analysis frameworks able to quantify the deformation of a shape into another in terms of the variation of real functions yields a new interpretation of the 3D shape similarity assessment and opens new perspectives. Indeed, while the classical approaches to similarity mainly quantify it as a numerical score, map‐based methods also define (dense) shape correspondences. After presenting in detail the theoretical foundations underlying these approaches, we classify them by looking at their most salient features, including the kind of structure and invariance properties they capture, as well as the distances and the output modalities according to which the similarity between shapes is assessed and returned. We also review the usage of these methods in a number of 3D shape application domains, ranging from matching and retrieval to annotation and segmentation. Finally, the most promising directions for future research developments are discussed.     

Eye movements induced by lateral acceleration steps. Effect of visual context and acceleration levels

Different extracellular matrix (ECM) molecules, when presented to hippocampal neurons in culture in a substrate-bound form, exert strikingly similar effects on the establishment of neuronal polarity, i.e., the growth of axon-like major neurites is favored, whereas extension of dendrite-like minor neurites is inhibited. To gain insight into the underlying signal transduction processes, we have investigated the effects of modulators of protein kinase activity on the morphology of neurons cultured on tenascin-R, tenascin-C, and laminin-entactin substrates. We found differential effects of broad-spectrum protein kinase inhibitors: H-7 promoted the growth of minor neurites, whereas H-8 reduced the growth of major neurites on ECM but not control substrates. In contrast, chelerythrine, a specific inhibitor of protein kinase C, selectively affected growth of both minor and major neurites on control, but not on ECM substrates. Finally, reagents which elevate intracellular cAMP levels facilitated growth of minor neurites and inhibited growth of major neurites and thus interfered with the establishment of a polarized phenotype on both ECM and control substrates. Our results suggest that protein kinases mediate the effects of ECM molecules on neuronal polarity and that different kinases control extension of axons and dendrites.