Piecewise Affine Registration of Biological Images for Volume Reconstruction

This manuscript tackles the reconstruction of 3D volumes via mono-modal registration of series of 2D biological images (histological sections, autoradiographs, cryosections, etc.). The process of acquiring these images typically induces composite transformations that we model as a number of rigid or affine local transformations embedded in an elastic one. We propose a registration approach closely derived from this model. Given a pair of input images, we first compute a dense similarity field between them with a block matching algorithm. We use as a similarity measure an extension of the classical correlation coefficient that improves the consistency of the field. A hierarchical clustering algorithm then automatically partitions the field into a number of classes from which we extract independent pairs of sub-images. Our clustering algorithm relies on the Earth mover’s distribution metric and is additionally guided by robust least-square estimation of the transformations associated with each cluster. Finally, the pairs of sub-images are, independently, affinely registered and a hybrid affine/non-linear interpolation scheme is used to compose the output registered image. We investigate the behavior of our approach on several batches of histological data and discuss its sensitivity to parameters and noise

Competitive segmentation of the hippocampus and the amygdala from MRI scans

The hippocampus and the amygdala are two brain structures which play a central role in several fundamental cognitive processes. Their segmentation from Magnetic Resonance Imaging (MRI) scans is a unique way to measure their atrophy in some neurological diseases, but it is made difficult by their complex geometry. Their simultaneous segmentation is considered here through a competitive homotopic region growing method. It is driven by relational anatomical knowledge, which enables to consider the segmentation of atrophic structures in a straightforward way. For both structures, this fast algorithm gives results which are comparable to manual segmentation with a better reproducibility. Its performances regarding segmentation quality, automation and computation time, are amongst the best published data.L’hippocampe et l’amygdale sont deux structures cérébrales intervenant dans plusieurs fonctions cognitives fondamentales. Leur segmentation, à partir de volumes d’imagerie par résonance magnétique (IRM), est un outil essentiel pour mesurer leur atteinte dans certaines pathologies neurologiques, mais elle est rendue difficile par leur géométrie complexe. Nous considérons leur segmentation simultanée par une méthode de déformation homotopique compétitive de régions. Celle-ci est guidée par des connaissances anatomiques relationnelles ; ceci permet de considérer directement des structures atrophiées. Rapide, l’algorithme donne, pour les deux structures, des résultats comparables à la segmentation manuelle avec une meilleure reproductibilité. Ses performances, concernant la qualité de la segmentation, le degré d’automatisation et le temps de calcul, sont parmi les meilleures de la littérature

Intra-operative Registration for Deep Brain Stimulation Procedures based on a Full Physics Head Model

International audienceBrain deformation is a factor of inaccuracy during stereotactic neurosurgeries. If this phenomenon is not considered in the pre-operative planning or intra-operatively, it could lead to surgical complications, side effects or ineffectiveness. In this paper, we present a patient-specific method to update the pre-operative planning based on a physical simulation of the brain shift. A minimization process estimates parameters of the simulation in order to compute the brain tissue deformation matching the partial data taken from intra-operative modalities. The simulation is based on a patient-specific biomechanical model of the brain and the cerebro-spinal fluid. We validate the method on a patient with a post-operative MRI

Intra-operative Registration for Stereotactic Procedures driven by a combined Biomechanical Brain and CSF Model

International audienceDuring stereotactic neurosurgery, the brain shift could affect the accuracy of the procedure. However, this deformation of the brain is not often considered in the pre-operative planning step or intra-operatively, and may lead to surgical complications, side effects or ineffectiveness. In this paper, we present a method to update the pre-operative planning based on a physical simulation of the brain shift. Because the simulation requires unknown input parameters, the method relies on a parameter estimation process to compute the intracranial state that matches the partial data taken from intra-operative modalities. The simulation is based on a biomechanical model of the brain and the cerebro-spinal fluid. In this paper, we show on an anatomical atlas that the method is numerically sound

Evaluation of driver models for left turn across path manoeuvres

Accidents at intersections are one of the most common causes of fatalities on roads. Statistics from the EU and the USA show that fatalities at intersections represent more than one fifth of all traffic fatalities. In particular, the left turn across the path of a vehicle coming from the opposite direction (LTAP/OD) is one of the riskiest situations at intersections. The goal of the thesis is to develop driver models describing human behaviour during left-turn-across path scenarios, for future use in active safety systems development for intersections. Video and vehicle dynamics data during daily driving were retrieved from the EuroFOT project database in order to find LTAP/OD scenarios suitable for the scope of the thesis. For the description of driver’s behaviour during the LTAP/OD scenario, two different driver modelling approaches have been considered: the Salvucci and Gray’s, which focuses on steering behaviour, and Nobukawa’s, which is based on vehicle acceleration. The work has been performed using MATLAB®, exploiting also genetic algorithms for model parameter optimization. The models describe the steering and speed behaviour reasonably well for the specific LTAP/OD events used in the model optimization and validation. However, generalization cannot be made across LTAP/OD as a scenario. Further efforts are required, e.g., to increase of number of intersections and number of drivers in the validation, to verify the reliability of the two models and develop it further. Once reliability has been established, the models may be used as part of the design of Intersection Driver Support Systems

Comparaison de trois méthodologies ESG : les bases de données extra-financières fournissent-elles la même information ?

L’objet de la recherche est d’étudier la convergence des notes ESG de trois organismes de notation extra-financière. Dans un contexte de tétranormalisation (Savall et Zardet, 2005), la validité et la conformité des ratings ESG, compte tenu des missions confiées aux agences, sont peu étudiées (Chatterji et al., 2016). L’étude porte sur un échantillon de 247 sociétés cotées européennes et 65 anglo-saxonnes lors des années 2009-2012. Elle évalue les différences d’approche des trois organismes. La méthodologie utilisée est l’analyse en composantes principales qui établit les corrélations entre les scores puis la régression longitudinale qui identifie les facteurs de différenciation observés.The aim of the research is to study the convergence of the ESG ratings of three non-financial rating organizations. In the context of tetrastandardization (Savall and Zardet, 2005), the validity and conformity of ESG ratings, given the missions entrusted to the agencies, are poorly studied (Chatterji et al., 2016). The study is based on a sample of 247 listed European companies and 65 Anglo-Saxons in the years 2009-2012. It assesses the differences in approach of the three organizations. The methodology used is the principal component analysis which establishes the correlations between the scores and then the longitudinal regression which identifies the differentiation factors observed

Valeur de marché et mesures comptables: les entreprises de la nouvelle économie française

Cet article s’intéresse à l’évaluation des entreprises de la nouvelle économie française. Il examine le lien entre leur valeur de marché et les principaux paramètres de mesure de la situation financière décrits dans les états financiers : le résultat, les flux de trésorerie et les capitaux propres. Les exercices 2000-2002 servent de cadre temporel à l’analyse. Cette recherche s’inscrit dans la lignée des études visant à montrer la pertinence des mesures comptables et l’utilité de l’information financière pour expliquer les valorisations boursières des sociétés. La méthodologie utilisée est celle des études d’association. Les résultats testés à l’aide de trois modèles montrent l’intérêt du résultat de l’exercice et du résultat opérationnel dans l’explication des valeurs de marché des entreprises.This paper provides further evidence on the financial valuation of French start-ups over the period 2000-2002. Using association studies, relevant indicators such as net income versus cash flows are used to explain market value and as proxies of growth opportunities. Results show the relevance of accounting models and figures, particularly the ability of net income and operating income to convey useful information for financial analysts in different business settings. These findings from three models show the importance of fundamental analysis when data are available