Shear thickening and migration in granular suspensions

We study the emergence of shear thickening in dense suspensions of non-Brownian particles. We combine local velocity and concentration measurements using Magnetic Resonance Imaging with macroscopic rheometry experiments. In steady state, we observe that the material is heterogeneous, and we find that that the local rheology presents a continuous transition at low shear rate from a viscous to a shear thickening, Bagnoldian, behavior with shear stresses proportional to the shear rate squared, as predicted by a scaling analysis. We show that the heterogeneity results from an unexpectedly fast migration of grains, which we attribute to the emergence of the Bagnoldian rheology. The migration process is observed to be accompanied by macroscopic transient discontinuous shear thickening, which is consequently not an intrinsic property of granular suspensions

Breast Ultra-Sound image segmentation: an optimization approach based on super-pixels and high-level descriptors

International audienceBreast cancer is the second most common cancer and the leading cause of cancer death among women. Medical imaging has become an indispensable tool for its diagnosis and follow up. During the last decade, the medical community has promoted to incorporate Ultra-Sound (US) screening as part of the standard routine. The main reason for using US imaging is its capability to differentiate benign from malignant masses, when compared to other imaging techniques. The increasing usage of US imaging encourages the development of Computer Aided Diagnosis (CAD) systems applied to Breast Ultra-Sound (BUS) images. However accurate delineations of the lesions and structures of the breast are essential for CAD systems in order to extract information needed to perform diagnosis. This article proposes a highly modular and flexible framework for segmenting lesions and tissues present in BUS images. The proposal takes advantage of optimization strategies using super-pixels and high-level de-scriptors, which are analogous to the visual cues used by radiologists. Qualitative and quantitative results are provided stating a performance within the range of the state-of-the-art

Les descripteurs d'un son Librairie Matlab SPL et fichiers de descriptions ".sig""

Le traitement du signal audio rapide travaille avec des descriptions compactes des sons plutôt qu'avec les sons eux-mêmes. Dans une première partie nous introduisons cette notion de description et nous proposons un état de l'art des différents types de description utilisés. Ces descriptions incorporent le plus souvent des quantités telles que l'énergie ou le spectre de puissance à court-terme. Cependant, énergie et puissance sont des concepts qui sont souvent confondus ou mal interprétés, et leur définition dépend des conventions de calcul qui ont été choisies pour les signaux numérisés. Nous rappelons dans une deuxième partie les définitions théoriques (physiques) de ces concepts, et nous proposons nos propres conventions de calcul. Nous définisson alors un ensemble de formules pour le calcul exact (i.e. cohérent avec leur définition physique) de l'énergie, de la puissance ou de la valeur RMS en dB SPL. Ces définitions sont implémentées dans une librairie Matlab (SPL) qui sert à calculer les descripteurs d'un fichier son, et les incorpore dans un fichier de description dont nous avons défini le format (.sig). La dernière partie de ce rapport décrit la syntaxe de ces fonctions. Finalement, la troisième partie de ce rapport décrit la stucture des fichiers .sig

A combined three-dimensional digitisation and subsurface defect detection data using active infrared thermography

International audienceIn recent years, NonDestructive Testing (NDT) systems have been upgraded with three-dimensional information. Indeed, combine the three-dimensional and thermal information allows a more meaningful analysis. In the literature, the data for NDT and three-dimensional (3D) reconstruction analysis are commonly acquired from independent systems. However, the use of two such systems leads to error analysis during the data registration. In an attempt to overcome such problems, we propose a single system based on active thermography approach using heat point-source stimulation to get the 3D digitization as well as subsurface defect detection. The experiments are conducted on steel and aluminum objects, and a combined 3D / thermal-information is presented

Direct observation of Dirac cones and a flatband in a honeycomb lattice for polaritons

Two-dimensional lattices of coupled micropillars etched in a planar semiconductor microcavity offer a workbench to engineer the band structure of polaritons. We report experimental studies of honeycomb lattices where the polariton low-energy dispersion is analogous to that of electrons in graphene. Using energy-resolved photoluminescence we directly observe Dirac cones, around which the dynamics of polaritons is described by the Dirac equation for massless particles. At higher energies, we observe p orbital bands, one of them with the nondispersive character of a flatband. The realization of this structure which holds massless, massive and infinitely massive particles opens the route towards studies of the interplay of dispersion, interactions, and frustration in a novel and controlled environment

Classification of SD-OCT Volumes with LBP: Application to DME Detection

This paper addresses the problem of automatic classification of Spectral Domain OCT (SD-OCT) data for automatic identification of patients with Diabetic Macular Edema (DME) versus normal subjects. Our method is based on Local Binary Patterns (LBP) features to describe the texture of Optical Coherence Tomography (OCT) images and we compare different LBP features extraction approaches to compute a single signature for the whole OCT volume. Experimental results with two datasets of respectively 32 and 30 OCT volumes show that regardless of using low or high level representations, features derived from LBP texture have highly discriminative power. Moreover, the experiments show that the proposed method achieves better classification performances than other recent published works

An optimization approach to segment breast lesions in ultra-sound images using clinically validated visual cues

International audienceAs long as breast cancer remains the leading cause of cancer deaths among female population world wide, developing tools to assist radiologists during the diagnosis process is necessary. However, most of the technologies developed in the imaging laboratories are rarely integrated in this assessing process, as they are based on information cues differing from those used by clinicians. In order to grant Computer Aided Diagnosis (CAD) systems with these information cues when performing non-aided diagnosis, better segmentation strategies are needed to automatically produce accurate delineations of the breast structures. This paper proposes a highly modular and flexible framework for segmenting breast tissues and lesions present in Breast Ultra-Sound (BUS) images. This framework relies on an optimization strategy and high-level de-scriptors designed analogously to the visual cues used by radiologists. The methodology is comprehensively compared to other sixteen published methodologies developed for segmenting lesions in BUS images. The proposed methodology achieves similar results than reported in the state-of-the-art

Wood fiber orientation assessment based on punctual laser beam excitation: A preliminary study

International audienceThe EU imposes standards for the use of wood in structural applications. Local singularities such as knots affect the wood mechanical properties. They can be revealed by looking at the wood fiber orientation. For this reason, many methods were proposed to estimate the orientation of wood fiber using optical means, X-rays, or scattering measurement techniques. In this paper, an approach to assess the wood fiber orientation based on thermal ellipsometry is developed. The wood part is punctually heated with a Nd-YAG Laser and the thermal response is acquired by an infrared camera. The thermal response is elliptical due to the propagation of the heat through and along the wood fibers. An experiment is presented to show the capacity of such techniques to assess fiber orientation on wood specimen. In addition, an appropriate algorithm is given to extract the orientation of the ellipse

Computer-Aided Detection and diagnosis for prostate cancer based on mono and multi-parametric MRI: A review

International audienceProstate cancer is the second most diagnosed cancer of men all over the world. In the last decades, new imaging techniques based on Magnetic Resonance Imaging (MRI) have been developed improving diagnosis.In practise, diagnosis can be affected by multiple factors such as observer variability and visibility and complexity of the lesions. In this regard, computer-aided detection and computer-aided diagnosis systemshave been designed to help radiologists in their clinical practice. Research on computer-aided systems specifically focused for prostate cancer is a young technology and has been part of a dynamic field ofresearch for the last ten years. This survey aims to provide a comprehensive review of the state of the art in this lapse of time, focusing on the different stages composing the work-flow of a computer-aidedsystem. We also provide a comparison between studies and a discussion about the potential avenues for future research. In addition, this paper presents a new public online dataset which is made available to theresearch community with the aim of providing a common evaluation framework to overcome some of the current limitations identified in this survey