O.: Non-rigid image registration using a hierarchical partition of unity finite element method

We use a Hierarchical Partition of Unity Finite Element Method (H-PUFEM) to represent and analyse the non-rigid deformation fields involved in multidimensional image registration. We make use of the Ritz-Galerkin direct variational method to solve non-rigid image registration problems with various deformation constraints. In this method, we directly seek a set of parameters that minimizes the objective function. We thereby avoid the loss of information that may occur when an Euler-Lagrange formulation is used. Experiments are conducted to demonstrate the advantages of our approach when registering synthetic images having little of or no localizing features. As a special case, conformal mapping problems can be accurately solved in this manner. We also illustrate our approach with an application to Cardiac Magnetic Resonance temporal sequences. 1

Neural networks for industrial vision applications

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Defect pairs and clusters related to the EL2 centre in GaAs

In this article, we attempt to consistently interpret Deep Level Transient Spectroscopy (DLTS), Electron Paramagnetic Resonance (EPR) and electrical conductivity experimental data for irradiated GaAs. Our analysis reveals the occurrence of an irradiation-induced single donor mid-gap level (MG) related to the AsGa antisite defect. We give evidence that MG can be identified with the deep level associated to the native bulk centre EL2. We make use of a model we have recently developed for the calculation of inter-defect phonon-assisted tunnelling rates. We calculate the nearest neighbour defect-induced hopping conductivities. In heavy dose irradiated GaAs, the DC conductivity is attributed to hopping between MG defects. Our calculations provide extremely good fits to the experimental results of Deng et al. for the DC electrical conductivity in GaAs induced by argon ion bombardment for temperatures ranging from around 20 K to 500 K. The phonon energy ħω (20 ± 2 meV) and Franck-Condon shift Sħω (145 ±10 meV) of MG needed to achieve this fit are in very good agreement with the ħω and Sħω values earlier determined for the native EL2 defect. The bulk AC hopping conductivity has also been calculated and found to agree well with experimental results of Mareš et al. for high purity semi-insulating GaAs. The corresponding low-frequency AC conductivity is attributed entirely to a homogeneous random distribution of native mid-gap donor defects EL2. We are also led to invoke the mid-gap level MG (identifiable with that of EL2) in order to account for DLTS results. In fast-electron irradiated n-GaAs, the two high temperature DLTS peaks E4 and E5 are both accounted for by two defect pairs each including an MG level component. In heavy-particle bombarded n-GaAs damage clusters including MG defects account for the experimentally recorded high temperature DLTS peak. For these defect pairs and clusters, our DLTS simulations correctly predict the observed peak positions and their dependence on the electric field

Prior-based Piecewise-smooth Segmentation by Template Competitive Deformation using Partitions of Unity

Abstract. We propose a new algorithm for two-phase, piecewise-smooth segmentation with shape prior. The image is segmented by a binary template that is deformed by a regular geometric transformation. The choice of the template together with the constraint on the transformation introduce the shape prior. In particular, the topology of the shape is preserved if the transformation is diffeomorphic. The deformation is guided by the maximization of the likelihood of foreground and background intensity models, so that we can refer to this approach as Competitive Deformation. In each region, the intensity is modelled as a smooth approximation of the original image. We represent the transformation using a Partition of Unity Finite Element Method, which consists in representing each component with polynomial approximations within local patches. A conformity constraint between the patches provides a way to control the globality of the deformation. We show several results on synthetic images, as well as on medical data from different modalities.

Fast solver for some computational imaging problems: A regularized weighted least-squares approach

International audienceIn this paper we propose to solve a range of computational imaging problems under a unified perspective of a regularized weighted least-squares (RWLS) framework. These problems include data smoothing and completion, edge-preserving filtering, gradient-vector flow estimation, and image registration. Although originally very different, they are special cases of the RWLS model using different data weightings and regularization penalties. Numerically, we propose a reconditioned conjugate gradient scheme which is particularly efficient in solving RWLS problems. We provide a detailed analysis of the system conditioning justifying our choice of the preconditioner that improves the convergence. This numerical solver, which is simple, scalable and parallelizable, is found to outperform most of the existing schemes for these imaging problems in terms of convergence rate. Copyright © 2014 Elsevier Inc. All rights reserved. Electronic version of this work can be found by using the following DOI: 10.1016/j.dsp.2014.01.00

Segmentation-free and multiscale-free extraction of medial information using gradient vector flow - Application to vascular structures

Gradient Vector Flow has become a popular method to recover medial information in medical imaging, in particular for vessels centerline extraction. This renewed interest has been motivated by its ability to proceed from gray-scale images, without prior segmentation. However, another interesting property lies in the diffusion process used to solve the corresponding variational problem. We propose a method to recover scale information in the context of vascular structures extraction, relying on analytical properties of the Gradient Vector Flow only, with no multiscale analysis. Through simple one-dimensional considerations, we demonstrate the ability of our approach to estimate the radii of the vessels with an error of 10% only in the presence of noise and less than 3% without noise. Our approach is evaluated on convolved bar-like templates and is illustrated on 2D X-ray angiographies. (c) 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. This paper is also available with the following DOI: http://dx.doi.org/DOI10.1109/ISBI.2012.6235533no

3D harmonic phase tracking with anatomical regularization

International audienceThis paper presents a novel algorithm that extends HARP to handle 3D tagged MRI images. HARP results were regularized by an original regularization framework defined in an anatomical space of coordinates. In the meantime, myocardium incompressibility was integrated in order to correct the radial strain which is reported to be more challenging to recover. Both the tracking and regularization of LV displacements were done on a volumetric mesh to be computationally efficient. Also, a window-weighted regression method was extended to cardiac motion tracking which helps maintain a low complexity even at finer scales. On healthy volunteers, the tracking accuracy was found to be as accurate as the best candidates of a recent benchmark. Strain accuracy was evaluated on synthetic data, showing low bias and strain errors under 5% (excluding outliers) for longitudinal and circumferential strains, while the second and third quartiles of the radial strain errors are in the (−5%,5%)(−5%,5%) range. In clinical data, strain dispersion was shown to correlate with the extent of transmural fibrosis. Also, reduced deformation values were found inside infarcted segments

Motion estimation in 3D echocardiography using smooth field registration

International audienceThis paper describes an algorithm for motion and deforma- tion quanti cation of 3D cardiac ultrasound sequences. The algorithm is based on the assumption that the deformation eld is smooth inside the myocardium. Thus, we assume that the displacement eld can be represented as the convolution of an unknown eld with a Gaussian kernel. We apply our algorithm to datasets with reliable ground truth: a set of synthetic sequences with known trajectories and a set of sequences of a mechanical phantom implanted with microsonometry crystals. The final publication is available at link.springer.co

Computational and physical phantom setups for the second cardiac motion analysis challenge (cMAC2)

International audienceThis paper describes the data setup of the second cardiac Motion Analysis Challenge (cMac2). The purpose of this challenge is to initiate a public data repository for the benchmark of motion and strain quantification algorithms on 3D ultrasound images. The data currently includes synthetic images that combine ultrasound and biomechanical simulators. We also collected sonomicrometry curves and ultrasound images acquired on a Polyvinyl alcohol phantom