A fast voxelization algorithm for trilinearly interpolated isosurfaces

International audienceIn this work we propose a new method for a fast incremental voxelization of isosurfaces obtained by the trilinear interpolation of 3D data. Our objective consists in the fast generation of subvoxelized iso-surfaces extracted by a point-based technique similar to the Dividing Cubes algorithm. Our technique involves neither an exhaustive scan search process nor a graph-based search approach when generating iso-surface points. Instead an optimized incremental approach is adopted here for a rapid isosurface extraction. With a sufficient sampling subdivision criteria around critical points, the extracted isosurface is both correct and topologically consistent with respect to the piece-wise trilinear interpolant. Furthermore, the discretiza-tion scheme used in our method ensures obtaining thin-one voxel width-isosurfaces as compared to the given by the Dividing Cubes algorithm. The resultant sub-voxelized isosurfaces are efficiently tested against all possible configurations of the trilinear interpolant and real-world datasets

Détection des croisements de fibre en IRM de diffusion par décomposition de tenseur : Approche analytique

National audienceL'IRM de diffusion (IRMd) est l'unique modalité qui permet d'explorer les structures neuronales de la substance blanche in-vivo et de manière non-invasive. La diffusion a d'abord été modélisée par le modèle du tenseur de diffusion du second ordre (DTI). Toutefois, ce modèle trouve rapidement ses limites dans les zones, nombreuses, où les fibres de la matière blanche se croisent. Pour surmonter cette limite et reconstruire les croisements de fibres, différentes approches ont été proposées telles que: l'imagerie à résonance magnétique (IRM) à haute résolution angulaire (HARDI) et les tenseurs d'ordre supérieur (HOT) ; ces méthodes permettent de reconstruire des fonctions telle que la fonction de distribution d'orientation de fibre (FOD) dont les maxima s'alignent sur les orientations des fibres multiples. Dans ce travail, on se propose d'extraire les directions des fibres caractérisées par les maxima de la fonction FOD. Pour cela, une approche analytique de décomposition de tenseur symétrique a été implémentée et efficacement adaptée pour extraire les directions des fibres avec précision. Différents résultats obtenus sur des données synthétiques et réelles illustrent l'efficacité de la méthode

Evaluation des méthodes d'extraction des orientations locales des faisceaux de fibres par analyse quantitative de la connectivité

International audienceRecovering of the fiber orientations in each voxel constitutes an important step for the fiber tracking algorithms. In fact, the reliability of the resulted connectivity depends on how well the local fiber orientations were extracted. Based on the tractography results we evaluated and compared different methods of fiber orientations extraction. Thus, we analyzed quantitatively the resulted connectivity by using the Tractometer tool. This later allows by measuring a number of metrics to quantify the connections reliability and the tractography performance. All the methods of fiber orientations extraction were evaluated on two types of tractography algorithms, deterministic and probabilistic algorithms. Furthermore, all of these methods have been executed on two types of data, high angular resolution data acquired with 60 gradient directions and low angular resolution data, acquired with 30 gradient directions. These two types of data were corrupted with a Ricien noise of ratio SNR=20, 10. In this article, we present the results obtained by our validation and comparison work.La détection des orientations locales des faisceaux de fibres constitue une étape importante pour les algorithmes de suivi de fibres (tractographie).En effet, la fiabilité de la connectivité résultante dépend de la qualité de l'extraction de ces orientations locales de fibres. Sur la base des résultats produits au niveau de la tractographie, nous avons évalué et comparé un ensemble d'algorithmes d'extraction des orientations des faisceaux de fibres. Une analyse quantitative de la connectivité a été ainsi réalisée en utilisant un outil appelé le Tractometer. Cet outil permet grâce à un certain nombre de métriques de quantifier la fiabilité des connexions reconstruites et aussi la performance des algorithmes de suivi de fibre utilisés. Toutes les méthodes d'extraction des orientations de fibres mises en oeuvre ont été évaluées sur la base des résultats de deux types d'algorithmes de tractographie, déterministe et probabiliste. De plus, l'ensemble de ces méthodes ont été exécutées sur deux types de données de diffusion, des données à haute résolution angulaire de 60 directions de gradient et des données à basse résolution angulaire de 30 directions de gradient, ces deux jeux de données ont été corrompus par un bruit Ricien d'un rapport SNR de 20 puis de 10. Dans cet article, nous présentons les résultats obtenus par ce travail de validation et de comparaison

A fast voxelization algorithm for trilinearly interpolated isosurfaces

International audienceIn this work we propose a new method for a fast incremental voxelization of isosurfaces obtained by the trilinear interpolation of 3D data. Our objective consists in the fast generation of subvoxelized iso-surfaces extracted by a point-based technique similar to the Dividing Cubes algorithm. Our technique involves neither an exhaustive scan search process nor a graph-based search approach when generating iso-surface points. Instead an optimized incremental approach is adopted here for a rapid isosurface extraction. With a sufficient sampling subdivision criteria around critical points, the extracted isosurface is both correct and topologically consistent with respect to the piece-wise trilinear interpolant. Furthermore, the discretiza-tion scheme used in our method ensures obtaining thin-one voxel width-isosurfaces as compared to the given by the Dividing Cubes algorithm. The resultant sub-voxelized isosurfaces are efficiently tested against all possible configurations of the trilinear interpolant and real-world datasets

Beyond Grid Portals and Towards SaaS A new access model for computational grids, in the MRI Brain context

International audienceAcigna-G is an ongoing research project to develop a new hybrid Grid SaaS architecture. CloudMRI is our proof-of-concept Acigna-G based SaaS Service for the Brain dMRI field. The main objective of such architecture is to provide local (Browser) and remote (Grid) intensive computational capabilities completly abstracted to the SaaS user. The result is a combination of an in Browser Rendering and Computation engine, interoperable REST-SOAP Grid Services, and interoperable web-grid authentication mechanisms. Such architecture can allow new types of SaaS Services, specifically for the dMRI Brain field

Use of Particle Swarm Optimization for ODF Maxima Extraction

International audienceFiber tracking is winning more and more interest in the neuroscience research field and clinical practice, for its ability in revealing the structural connectivity; the quality of the fiber tracking depends in great extent, on fiber directions extraction The PSO algorithm could give good approximation of these directions

A Hybrid Algorithm for DAG Application Scheduling on Computational Grids

International audienceIn the late three decades, grid computing has emerged as a new field providing a high computing performance to solve larger scale computational demands. Because Directed Acyclic Graph (DAG) application scheduling in a distributed environment is a NP-Complete problem, meta-heuristics are introduced to solve this issue. In this paper, we propose to hybridize two well-known heuristics. The first one is the Heterogeneous Earliest Finish Time (HEFT) heu-ristic which determines a static scheduling for a DAG in a heterogeneous environment. The second one is Particle Swarm Optimization (PSO) which is a sto-chastic meta-heuristic used to solve optimization problems. This hybridization aims to minimize the makespan (i.e., overall competition time) of all the tasks within the DAG. The experimental results that have been conducted under hy-bridization show that this approach improves the scheduling in terms of completion time compared to existing algorithms such as HEFT

Crossing Fibers Detection with an Analytical High Order Tensor Decomposition

International audienceDiffusion magnetic resonance imaging (dMRI) is the only technique to probe in vivo and noninvasively the fiber structure of human brain white matter. Detecting the crossing of neuronal fibers remains an exciting challenge with an important impact in tractography. In this work, we tackle this challenging problem and propose an original and efficient technique to extract all crossing fibers from diffusion signals. To this end, we start by estimating, from the dMRI signal, the so-called Cartesian tensor fiber orientation distribution (CT-FOD) function, whose maxima correspond exactly to the orientations of the fibers. The fourth order symmetric positive definite tensor that represents the CT-FOD is then analytically decomposed via the application of a new theoretical approach and this decomposition is used to accurately extract all the fibers orientations. Our proposed high order tensor decomposition based approach is minimal and allows recovering the whole crossing fibers without any a priori information on the total number of fibers. Various experiments performed on noisy synthetic data, on phantom diffusion, data and on human brain data validate our approach and clearly demonstrate that it is efficient, robust to noise and performs favorably in terms of angular resolution and accuracy when compared to some classical and state-of-the-art approaches

Workflow scheduling with data transfer optimization and enhancement of reliability in cloud data centers

International audienc

On the optimal reconstruction of dMRI images with multi-coil acquisition system

International audienc