Change detection is of paramount importance in medical imaging, serving as a non-invasive quantifiable powerful tool in diagnosis and in assessment of the outcome of treatment of tumors. We present a new quantitative method for detecting... more
Change detection is of paramount importance in medical imaging, serving as a non-invasive quantifiable powerful tool in diagnosis and in assessment of the outcome of treatment of tumors. We present a new quantitative method for detecting changes in volumetric medical data and in clustering of anatomical structures, based on assessment of volumetric distortions that are required in order to deform a test three-dimensional medical dataset segment onto its previously-acquired reference, or a given prototype in the case clustering. Unlike the voxel-based classical techniques of shape comparison, our algorithm operates on tetrahedral meshes and can, therefore be applied on both closed, simply-connected, surfaces and in volumetric domains with more sophisticated boundaries.
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be suitable for sub-Gaussian sources, is inconsistent for some of such sources (wherein QXQSTU `—`QXUQSP). With the only exception of 9
Piecewise Fractional Brownian motion (p-fBm) is a continuous non-stationary Gaussian process having stationary Gaussian increments, named piecewise fractional Gaussian noise (p-fGn). Unlike fractional Brownian motion (fBm) governed by a... more
Piecewise Fractional Brownian motion (p-fBm) is a continuous non-stationary Gaussian process having stationary Gaussian increments, named piecewise fractional Gaussian noise (p-fGn). Unlike fractional Brownian motion (fBm) governed by a unique parameter (Hurst exponent), p-fBm is defined by three parameters: the Hurst exponent in low frequencies, the Hurst exponent in high frequencies and the threshold frequency, which separates the two regimes. In this paper, we present a synthesis method that generates a finite approximation of p-fBm series. Moreover, we analyze the synthesized p-fBm series and test the Gaussianity of both p-fBm and p-fGn. We test the stationarity of the first order increments (p-fGn) and explore an approach to estimation of the process Hurst parameters. Our contribution is relevant to modeling and analysis of certain textures that are characteristic of certain medical and other natural images.
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Analyzing Action Representations.- The Systems Theory of Contact.- An Associative Perception-Action Structure Using a Localized Space Variant Information Representation.- The Structure of Colorimetry.- Fast Calculation Algorithms of... more
Analyzing Action Representations.- The Systems Theory of Contact.- An Associative Perception-Action Structure Using a Localized Space Variant Information Representation.- The Structure of Colorimetry.- Fast Calculation Algorithms of Invariants for Color and Multispectral Image Recognition.- Modelling Motion: Tracking, Analysis and Inverse Kinematics.- The Lie Model for Euclidean Geometry.- On the Geometric Structure of Spatio-temporal Patterns.- Learning Geometric Transformations with Clifford Neurons.- Hurwitzion Algebra and its Application to the FFT Synthesis.- Diffusion-Snakes Using Statistical Shape Knowledge.- The Multidimensional Isotropic Generalization of Quadrature Filters in Geometric Algebra.- Sparse Feature Maps in a Scale Hierarchy.- Estimation and Tracking of Articulated Motion Using Geometric Algebra.- Geometric Properties of Central Catadioptric Projections.- Lie-Theory and Dynamical Illumination Changes.- A Group Theoretical Formalization of Contact Motion.- Periodic Pattern Analysis under Affine Distortions Using Wallpaper Groups.- Wavelet Filter Design via Linear Independent Basic Filters.- Lie Group Modeling of Nonlinear Point Set Shape Variability.- Symmetries in World Geometry and Adaptive System Behaviour.- Pose Estimation in the Language of Kinematics.- Algebraic Frames for Commutative Hyperharmonic Analysis of Signals and Images.- Gabor-Space Geodesic Active Contours.- Color Image Enhancement by a Forward-and-Backward Adaptive Beltrami Flow.- Point-Based Registration Assuming Affine Motion.- Extended Kalman Filter Design for Motion Estimation by Point and Line Observations.
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ABSTRACT
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ABSTRACT An algorithm for the estimation and reconstruction of event related signals corrupted by colored noise (e.g. evoked potentials, masked by EEG activity and additional sources of clutter and noise) is proposed. The local... more
ABSTRACT An algorithm for the estimation and reconstruction of event related signals corrupted by colored noise (e.g. evoked potentials, masked by EEG activity and additional sources of clutter and noise) is proposed. The local Karhunen-Loeve (LKL) basis, derived from the noisy signal local autocorrelation function, is used for optimal signal representation (in minimum mean squared error-MMSE-sense). The vector space of the noisy signal is decomposed by the LKL transform into the corresponding complementary orthogonal subspaces, i.e. the signal-plus-noise and the noise only. The event related signal is estimated from the signal-plus-noise subspace by modifying the corresponding LKL components with a Wiener-like gain function
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Research Interests: Medicine, Humans, Female, Saccades, Male, and 7 moreReaction Time, Eye Movements, Hyperthyroidism, Middle Aged, Adult, Time Factors, and Eye Movement
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Research Interests: Computer Science, Artificial Intelligence, Computer Vision, Visual perception, Medicine, and 10 moreImage Analysis (Mathematics), Peripheral vision, Humans, Contrast sensitivity, Spatial Frequency, Optical physics, Optometry and Ophthalmology, Adult, Electrical And Electronic Engineering, and image resolution
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Received January 27, 1987; accepted June 29, 1987 Signal representation by its points of crossing of a reference signal is considered with emphasis on applications to images. Some results that are elaborated for the representation of... more
Received January 27, 1987; accepted June 29, 1987 Signal representation by its points of crossing of a reference signal is considered with emphasis on applications to images. Some results that are elaborated for the representation of one-dimensional signals by their sine-wave ...
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Research Interests: Mechanical Engineering, Mathematics, Applied Mathematics, Computer Science, Control Theory, and 15 moreOptimal Control, Control, Automatic Control, Robust control, Control Systems, Control system, State Space, Feedback, Active Vision, Linear System, Electrical And Electronic Engineering, Switches, State Space Methods, Discrete time, and Linear optimization
Dark adapted and progressively light adapted electroretinograms (ERGs) were recorded from 34 normals and from 45 glaucoma patients. To enhance the oscillatory potentials (OP) the ERGs were highpass-filtered. The OP were characterized by... more
Dark adapted and progressively light adapted electroretinograms (ERGs) were recorded from 34 normals and from 45 glaucoma patients. To enhance the oscillatory potentials (OP) the ERGs were highpass-filtered. The OP were characterized by two indices: their root-mean-square value and the inter-flash interval for which the maximal amplitude was obtained. In most of the glaucomatous OP, 50 of 81 eyes, both indices were abnormal, in 22 one parameter was abnormal and only in 9 were both parameters normal. In 13 of the 14 OP recorded from the opposite ('normal') eye of patients with unilateral glaucoma either one or both of the indices were abnormal. These findings indicate that the damage to the retina in glaucoma may extend more distally than the ganglion cell layer and that subclinical changes might be revealed by OP changes.
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A general model for an adaptive neural encoder relating the output firing frequency to input stimulus is presented. The model is based on an "integrate and fire at threshold" scheme and includes cumulative inhibitory... more
A general model for an adaptive neural encoder relating the output firing frequency to input stimulus is presented. The model is based on an "integrate and fire at threshold" scheme and includes cumulative inhibitory feedback as well as output rate dependent threshold control.
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ABSTRACT This paper addresses nonlinear cross diffusion systems in the context of image processing tasks. While nonlinear diffusion is a cele-brated tool, it still lacks a proper theoretical foundation is some areas. Especially the... more
ABSTRACT This paper addresses nonlinear cross diffusion systems in the context of image processing tasks. While nonlinear diffusion is a cele-brated tool, it still lacks a proper theoretical foundation is some areas. Especially the question of existence of solutions for edge preserving equa-tions like the Perona-Malik equation has not been dealt with satisfacto-rily: For the pure edge preserving equation it is known that no global solution exists (unless the initial value is very smooth), while well posed variants like space averaging in the sense of Catté, Lions, Morel and Coll introduce artificial smoothing to prevent the blowup of the gradient. By considering cross-diffusion systems we are able to provide a diffu-sion equation which fully degenerates, for which the existence of global bounded solutions can be shown. This is achieved by providing smoothed derivative information intrinsically.
The generators of auditory brainstem evoked potentials (ABEPs) are generally agreed to be located between the auditory nerve and upper pons. Thus, they are all located within a few cm from the center of the head. Three-channel... more
The generators of auditory brainstem evoked potentials (ABEPs) are generally agreed to be located between the auditory nerve and upper pons. Thus, they are all located within a few cm from the center of the head. Three-channel Lissajous' trajectory (3CLT) provides the amplitude and orientation of a centrally located equivalent dipole of surface recorded activity. Volume conductor theory predicts decreased spatial resolution of source estimation the deeper the source. In this study we compared source estimates obtained with 3CLT, using three orthogonal differential channels, with those obtained with two other source estimation methods: i) setting the generators at their known anatomical coordinates and calculating orientation and magnitude of the source (dipole localization method--DLM); ii) estimation of all source parameters, including the number of sources by wavelet-type decomposition, without assumptions on the location of the sources (multiple source estimate--MSE). 3CLT, DLM and MSE all converged on magnitudes and orientations that were not significantly different from each other, and locations that were within a few cm of each other. In conclusion, although 3CLT can only estimate a single, centrally located equivalent dipole, in the specific case of ABEPs, it provides the same information available from the more demanding source estimate methods. In addition to the considerable saving in recording channels, 3CLT is reference-independent and thus avoids ambiguities resulting from the choice of reference.
Research Interests: Physics, Electrophysiology, Medicine, Humans, Dipole, and 3 moreClinical Sciences, Electrodes, and Scalp
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A method and algorithm of ∞attening of folded surfaces for two-dimensional representation and analysis of medical images are presented. The method is based on extension of classical results of Gehring and Vaisala regarding the existence... more
A method and algorithm of ∞attening of folded surfaces for two-dimensional representation and analysis of medical images are presented. The method is based on extension of classical results of Gehring and Vaisala regarding the existence of quasi-conformal and quasi-isometric mappings. The proposed algorithm is basically local and, therefore, suitable for extensively folded surfaces encountered in medical imaging. The theory and
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A new Combinatorial Ricci curvature and Laplacian opera- tors for grayscale images are introduced and tested on 2D medical im- ages. These notions are based upon more general concepts developed by R. Forman. Further applications are also... more
A new Combinatorial Ricci curvature and Laplacian opera- tors for grayscale images are introduced and tested on 2D medical im- ages. These notions are based upon more general concepts developed by R. Forman. Further applications are also suggested.
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Natural stochastic textures (NSTs), characterized by their fine details, are prone to corruption by artifacts, introduced during the image acquisition process by the combined effect of blur and noise. While many successful algorithms... more
Natural stochastic textures (NSTs), characterized by their fine details, are prone to corruption by artifacts, introduced during the image acquisition process by the combined effect of blur and noise. While many successful algorithms exist for image restoration and enhancement, the restoration of natural textures and textured images based on suitable statistical models has yet to be further improved. We examine the statistical properties of NST using three image databases. We show that the Gaussian distribution is suitable for many NST, while other natural textures can be properly represented by a model that separates the image into two layers; one of these layers contains the structural elements of smooth areas and edges, while the other contains the statistically Gaussian textural details. Based on these statistical properties, an algorithm for the denoising of natural images containing NST is proposed, using patch-based fractional Brownian motion model and regularization by means...