Development of an Advanced 3D Cone Beam Tomographic System

While 2D x-ray CT is now commonly used for NDT applications, the interest in 3D x-ray cone beam tomography has significantly increased over the last few years [1,2]. The need to reduce acquisition time for industrial applications, or radiation dose to patients for medical applications, led engineers to develop a new type of tomograph using x-ray beams more efficiently. Thanks to a high spatial resolution, the 3D x-ray CT allows greater knowledge of the object structure. This understanding is necessary to study and improve industrial production of high technology materials. Therefore, 3D x-ray CT is well suited for the study of materials with structural anomalies, such as technical ceramics [2]

X-Ray Cone Beam Tomography with Two Tilted Circular Trajectories

Recently 3-D cone-beam tomography has become of interest for the nondestructive evaluation of advanced materials. The main field of application in nondestructive testing is the evaluation of structural ceramics. Study of such materials implies high density resolution and high sensitivity to cracks. In fact, with a single circular source trajectory, when the cone-beam aperture increases, density is underestimated and cone shaped artifacts may appear at interfaces in the sample even at relatively small aperture [1–3]. These artifacts limit the thickness we can examine with a planar source trajectory. To maintain optimal reconstruction accuracy with a circular source trajectory, the angular aperture must remain within ±10°. However Kudo and Saito [4] showed that this limit can be slightly overcome by using a special interpolation of the shadow area. But to examine greater thicknesses and to maintain resolution, we must widen the cone-beam aperture thereby decreasing accuracy. To overcome these aperture limitations, Tuy [5] introduced the double circular source trajectory idea

Robustesse des approches chimiométriques pour la reconstruction de profils moléculaires

Ce papier traite des approches chimiométriques pour la reconstruction de profils moléculaires. La quantification de protéines du sang est réalisée à partir du traitement par analyse factorielle de spectrogrammes issus d'une chaîne d'analyse contenant une colonne de nano-chromatographie et un spectromètre de masse. Nous nous intéressons plus particulièrement à la comparaison de la robustesse des méthodes de régression de type Unfold-PLS, N-PLS et PARAFAC vis-à-vis du problème de décalage temporel des pics contenus dans les spectrogrammes. Les méthodes multidimensionnelles type N-PLS et PARAFAC fournissent de meilleurs résultats ce qui permet d'envisager une quantification des protéines avec une plus grande tolérance sur le recalage des pics en temps de rétention

Reconstruction en imagerie gamma à partir d'acquisitions multi-énergie

Le problème traité concerne la reconstruction de la distribution 3D de sources radioactives lors d'examens scintigraphiques. Nous proposons une approche de reconstruction permettant d'exploiter les informations issues de capteurs spectrométriques et en particulier les informations portées par le rayonnement diffusé pour améliorer la qualité des images. La communication présente les résultats obtenus par une approche d'inversion s'appuyant sur un modèle précis de la physique de formation des projections en imagerie gamma. Cette méthode a été baptisée SCARECO (scatter recovery)

Reconstruction bayésienne de profils moléculaires

L'étude des protéines laisse entrevoir de grands espoirs pour la médecine de demain. Cependant pour répondre à ces promesses, les méthodes actuelles doivent gagner en sensibilité, en spécificité et en robustesse. Dans cette optique, le CEA développe un laboratoire sur puce et des méthodes de traitement numérique dédiées aux analyses protéomiques par LC-MS. Nous présentons dans cet article une approche bayésienne pour la reconstruction des profils de concentrations de protéines. Dans un premier temps nous proposons un modèle pour le dispositif de mesure complet. Puis nous décrivons une méthode d'estimation des concentrations de protéines présentes, les paramètres instrumentaux étant fixés. Enfin nous estimons conjointement les concentrations et les paramètres instrumentaux

Trkalian fields: ray transforms and mini-twistors

We study X-ray and Divergent beam transforms of Trkalian fields and their relation with Radon transform. We make use of four basic mathematical methods of tomography due to Grangeat, Smith, Tuy and Gelfand-Goncharov for an integral geometric view on them. We also make use of direct approaches which provide a faster but restricted view of the geometry of these transforms. These reduce to well known geometric integral transforms on a sphere of the Radon or the spherical Curl transform in Moses eigenbasis, which are members of an analytic family of integral operators. We also discuss their inversion. The X-ray (also Divergent beam) transform of a Trkalian field is Trkalian. Also the Trkalian subclass of X-ray transforms yields Trkalian fields in the physical space. The Riesz potential of a Trkalian field is proportional to the field. Hence, the spherical mean of the X-ray (also Divergent beam) transform of a Trkalian field over all lines passing through a point yields the field at this point. The pivotal point is the simplification of an intricate quantity: Hilbert transform of the derivative of Radon transform for a Trkalian field in the Moses basis. We also define the X-ray transform of the Riesz potential (of order 2) and Biot-Savart integrals. Then, we discuss a mini-twistor respresentation, presenting a mini-twistor solution for the Trkalian fields equation. This is based on a time-harmonic reduction of wave equation to Helmholtz equation. A Trkalian field is given in terms of a null vector in C3 with an arbitrary function and an exponential factor resulting from this reduction.Comment: 37 pages, http://dx.doi.org/10.1063/1.482610

Nanoinformatics: developing new computing applications for nanomedicine

Nanoinformatics has recently emerged to address the need of computing applications at the nano level. In this regard, the authors have participated in various initiatives to identify its concepts, foundations and challenges. While nanomaterials open up the possibility for developing new devices in many industrial and scientific areas, they also offer breakthrough perspectives for the prevention, diagnosis and treatment of diseases. In this paper, we analyze the different aspects of nanoinformatics and suggest five research topics to help catalyze new research and development in the area, particularly focused on nanomedicine. We also encompass the use of informatics to further the biological and clinical applications of basic research in nanoscience and nanotechnology, and the related concept of an extended ?nanotype? to coalesce information related to nanoparticles. We suggest how nanoinformatics could accelerate developments in nanomedicine, similarly to what happened with the Human Genome and other -omics projects, on issues like exchanging modeling and simulation methods and tools, linking toxicity information to clinical and personal databases or developing new approaches for scientific ontologies, among many others

A Transdimensional Bayesian Approach to Ultrasonic Travel-time Tomography for Non-Destructive Testing

Traditional imaging algorithms within the ultrasonic non-destructive testing community typically assume that the material being inspected is primarily homogeneous, with heterogeneities only at sub-wavelength scales. When the medium is of a more generally heterogeneous nature, this assumption can contribute to the poor detection, sizing and characterisation of any defects. Prior knowledge of the varying velocity fields within the component would allow more accurate imaging of defects, leading to better decisions about how to treat the damaged component. This work endeavours to reconstruct the inhomogeneous velocity fields of random media from simulated ultrasonic phased array data. This is achieved via application of the reversible-jump Markov chain Monte Carlo method: a sampling-based approach within a Bayesian framework. The inverted maps are then used in conjunction with an imaging algorithm to correct for deviations in the wave speed, and the reconstructed flaw images are then used to quantitatively measure the success of this methodology. Using full matrix capture data arising from a finite element simulation of a phased array inspection of a heterogeneous component, a six-fold improvement in flaw location is achieved by taking into account the reconstructed velocity map which exploits almost no \textit{a priori} knowledge of the material's internal structure. Receiver operating characteristic curves are then calculated to demonstrate the enhanced probability of detection achieved when the material map is accounted for