Chambres d’ionisation en Protonthérapie et Hadronthérapie

In the framework of the ARCHADE project (Advanced Resource Center for HADrontherapyin Europe), a research project in Carbone ion beam therapy and clinicalProtontherapy, this work investigates the beam monitoring and dosimetry aspects of ionbeam therapy. The main goal, here, is to understand the operating mode of air ionizationchambers, the detectors used for such applications. This study starts at a very fundamentallevel as the involved physical and chemical parameters of air were measured invarious electric field conditions with dedicated setups and used to produce a simulationtools aiming at reproducing the operating response in high intensity PBS (Pencil BeamScanning) coming from IBA’s (Ion Beam Applications) next generation of proton beamaccelerators. In addition, an ionization chamber-based dosimetry equipment was developed,DOSION III, for radiobiology studies conducted at GANIL under the supervisionof the CIMAP laboratory.Dans le cadre du projet ARCHADE (Advanced Resource Center for HADrontherapyin Europe), projet de recherche en thérapie par ions Carbone et en traitement Proton,ce travail de thèse s’intéresse aux aspects de contrôle faisceau et de dosimétrie autourdes chambres d’ionisation. L’objectif est de proposer une compréhension profonde de laréponse de tels détecteurs aux faisceaux utilisés en Hadronthérapie et plus particulièrementaux faisceaux issus des machines de Protonthérapie PBS (Pencil Beam Scanning)de nouvelle génération de l’entreprise Belge IBA (Ion Beam Applications). Cette étudepasse par la mesure des paramètres physico-chimiques fondamentaux de l’air utilisé parces instruments puis par l’implémentation de ces mêmes paramètres dans un outil desimulation. Parallèlement à ce travail, un dispositif également basé sur les chambresd’ionisation a été développé, DOSION III, afin de répondre aux besoins de contrôle dosimétriquedes expériences de radiobiologie ayant lieu au GANIL sous la responsabilitédu CIMAP

Bregman Voronoi Diagrams: Properties, Algorithms and Applications

The Voronoi diagram of a finite set of objects is a fundamental geometric structure that subdivides the embedding space into regions, each region consisting of the points that are closer to a given object than to the others. We may define many variants of Voronoi diagrams depending on the class of objects, the distance functions and the embedding space. In this paper, we investigate a framework for defining and building Voronoi diagrams for a broad class of distance functions called Bregman divergences. Bregman divergences include not only the traditional (squared) Euclidean distance but also various divergence measures based on entropic functions. Accordingly, Bregman Voronoi diagrams allow to define information-theoretic Voronoi diagrams in statistical parametric spaces based on the relative entropy of distributions. We define several types of Bregman diagrams, establish correspondences between those diagrams (using the Legendre transformation), and show how to compute them efficiently. We also introduce extensions of these diagrams, e.g. k-order and k-bag Bregman Voronoi diagrams, and introduce Bregman triangulations of a set of points and their connexion with Bregman Voronoi diagrams. We show that these triangulations capture many of the properties of the celebrated Delaunay triangulation. Finally, we give some applications of Bregman Voronoi diagrams which are of interest in the context of computational geometry and machine learning.Comment: Extend the proceedings abstract of SODA 2007 (46 pages, 15 figures

Parallel Mapper

The construction of Mapper has emerged in the last decade as a powerful and effective topological data analysis tool that approximates and generalizes other topological summaries, such as the Reeb graph, the contour tree, split, and joint trees. In this paper, we study the parallel analysis of the construction of Mapper. We give a provably correct parallel algorithm to execute Mapper on multiple processors and discuss the performance results that compare our approach to a reference sequential Mapper implementation. We report the performance experiments that demonstrate the efficiency of our method

FastJet user manual

FastJet is a C++ package that provides a broad range of jet finding and analysis tools. It includes efficient native implementations of all widely used 2-to-1 sequential recombination jet algorithms for pp and e+e- collisions, as well as access to 3rd party jet algorithms through a plugin mechanism, including all currently used cone algorithms. FastJet also provides means to facilitate the manipulation of jet substructure, including some common boosted heavy-object taggers, as well as tools for estimation of pileup and underlying-event noise levels, determination of jet areas and subtraction or suppression of noise in jets.Comment: 69 pages. FastJet 3 is available from http://fastjet.fr

Comparative validation of single-shot optical techniques for laparoscopic 3-D surface reconstruction

Intra-operative imaging techniques for obtaining the shape and morphology of soft-tissue surfaces in vivo are a key enabling technology for advanced surgical systems. Different optical techniques for 3-D surface reconstruction in laparoscopy have been proposed, however, so far no quantitative and comparative validation has been performed. Furthermore, robustness of the methods to clinically important factors like smoke or bleeding has not yet been assessed. To address these issues, we have formed a joint international initiative with the aim of validating different state-of-the-art passive and active reconstruction methods in a comparative manner. In this comprehensive in vitro study, we investigated reconstruction accuracy using different organs with various shape and texture and also tested reconstruction robustness with respect to a number of factors like the pose of the endoscope as well as the amount of blood or smoke present in the scene. The study suggests complementary advantages of the different techniques with respect to accuracy, robustness, point density, hardware complexity and computation time. While reconstruction accuracy under ideal conditions was generally high, robustness is a remaining issue to be addressed. Future work should include sensor fusion and in vivo validation studies in a specific clinical context. To trigger further research in surface reconstruction, stereoscopic data of the study will be made publically available at www.open-CAS.com upon publication of the paper

Robust Poisson Surface Reconstruction

Abstract. We propose a method to reconstruct surfaces from oriented point clouds with non-uniform sampling and noise by formulating the problem as a convex minimization that reconstructs the indicator func-tion of the surface’s interior. Compared to previous models, our recon-struction is robust to noise and outliers because it substitutes the least-squares fidelity term by a robust Huber penalty; this allows to recover sharp corners and avoids the shrinking bias of least squares. We choose an implicit parametrization to reconstruct surfaces of unknown topology and close large gaps in the point cloud. For an efficient representation, we approximate the implicit function by a hierarchy of locally supported basis elements adapted to the geometry of the surface. Unlike ad-hoc bases over an octree, our hierarchical B-splines from isogeometric analysis locally adapt the mesh and degree of the splines during reconstruction. The hi-erarchical structure of the basis speeds-up the minimization and efficiently represents clustered data. We also advocate for convex optimization, in-stead isogeometric finite-element techniques, to efficiently solve the min-imization and allow for non-differentiable functionals. Experiments show state-of-the-art performance within a more flexible framework.