Emmanuel Papadakis

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In this paper we investigate Isotropic Multiresolution Analysis(IMRA), isotropic refinable functions, and wavelets. The main results are the characterization of IMRAs in terms of the Lax-Wiener Theorem, and the characterization of isotropic refinable functions in terms of the support of their Fourier transform. As an immediate consequence of these results,(More)
The challenges faced in analyzing optical imaging data from neurons include a low signal-to-noise ratio of the acquired images and the multiscale nature of the tubular structures that range in size from hundreds of microns to hundreds of nanometers. In this paper, we address these challenges and present a computational framework for an automatic,(More)
In this paper we present a set of 3D-rigid motion invariant texture features. We experimentally establish that when they are combined with mean attenuation intensity differences the new augmented features are capable of discriminating normal from abnormal liver tissue in arterial phase contrast enhanced X-ray CT–scans with high sensitivity and specificity.(More)
We present a general mathematical theory for lifting frames that allows us to modify existing filters to construct new ones that form Parseval frames. We apply our theory to design nonseparable Parseval frames from separable (tensor) products of a piecewise linear spline tight frame. These new frame systems incorporate the weighted average operator, the(More)
—In this paper, we present a novel framework for quantifying physiological stress at a distance via thermal imaging. The method captures stress-induced neurophysiological responses on the perinasal area that manifest as transient perspiration. We have developed two algorithms to extract the perspiratory signals from the thermophysiological imagery. One is(More)
  • Manos Papadakis, Bernhard G Bodmann, Simon K Alexander, Deborah Vela, Shikha Baid, Alex A Gittens +11 others
  • 2008
We analyze localized textural consistencies in high-resolution X-ray CT scans of coronary arteries to identify the appearance of diagnostically relevant changes in tissue. For the efficient and accurate processing of CT volume data, we use fast wavelet algorithms associated with three-dimensional isotropic multiresolution wavelets that implement a(More)
In this paper, we construct a new class of deformable models using new biorthogonal wavelets, named Generalized Hermite Distributed Approximating Functional (g-HDAF) Wavelets. The scaling functions of this new family are symmetric and the corresponding wavelets optimize their smoothness for a given number of vanishing moments. In addition, we embed these(More)
This paper studies the problem of 3-D rigid-motion-invariant texture discrimination for discrete 3-D textures that are spatially homogeneous by modeling them as stationary Gaussian random fields. The latter property and our formulation of a 3-D rigid motion of a texture reduce the problem to the study of 3-D rotations of discrete textures. We formally(More)
Centerline tracing of dendritic structures in confocal images of neurons is an essential tool for the construction of a geometric representation of a neuronal network. In this paper, we propose a novel algorithm (ORION 2) for centerline extraction that is both highly accurate and computationally efficient. The main novelty of the proposed method is the use(More)
We construct examples of non-separable Isotropic Multiresolution Analyses (IMRA) for L 2 (R d). We develop a wave equation based poststack depth migration scheme using the frames arising from IMRA. If we discretise the signal at only one resolution level, then the method reduces to a so-called explicit scheme (see for example [8, 10]). The multiscale(More)