Automated multimodal volume registration based on supervised 3D anatomical landmark detection

We propose a new method for automatic 3D multimodal registration based on anatomical landmark detection. Landmark detectors are learned independantly in the two imaging modalities using Extremely Randomized Trees and multi-resolution voxel windows. A least-squares fitting algorithm is then used for rigid registration based on the landmark positions as predicted by these detectors in the two imaging modalities. Experiments are carried out with this method on a dataset of pelvis CT and CBCT scans related to 45 patients. On this dataset, our fully automatic approach yields results very competitive with respect to a manually assisted state-of-the-art rigid registration algorithm

Functional imaging and radiotherapy

peer reviewedLes progrès technologiques réalisés par l’image- rie médicale l’ont placée au centre de la prise en charge des patients oncologiques, tant au niveau du diagnostic, du pro - nostic et du suivi que dans la prise en charge thérapeutique. En effet, l’imagerie représente, à l’heure actuelle, la pierre angulaire des traitements de radiothérapie. Les objectifs du radiothérapeute sont d’irradier le plus précisément possible la tumeur à dose curative, tout en évitant les organes sains. Pour y arriver, le radiothérapeute utilise de façon routinière l’imagerie anatomique (Scanner et IRM). Depuis quelques années, le développement des différentes imageries métabo - liques et fonctionnelles, comme l’imagerie par émission de positons (PET-CT) et la résonnance magnétique fonctionnelle, ouvrent de nouvelles possibilités thérapeutiques grâce aux informations qu’elles apportent sur la biologie des tumeurs. Cet article décrit, de manière non exhaustive, les différentes imageries anatomiques et métaboliques à la disposition du radiothérapeute

Automata-based Representations for the Verification of Hybrid Systems

peer reviewe

On the Use of Weak Automata for Deciding Linear Arithmetic with Integer and Real Variables

peer reviewedThis paper considers finite-automata based algorithms for handling linear arithmetic with both real and integer variables. Previous work has shown that this theory can be dealt with by using finite automata on in finite words, but this involves some difficult and delicate to implement algorithms. The contribution of this paper is to show, using topological arguments, that only a restricted class of automata on in finite words are necessary for handling real and integer linear arithmetic. This allows the use of substantially simpler algorithms and opens the path to the implementation of a usable system for handling this combined theory

Orthanc

Orthanc is a lightweight, RESTful DICOM server for healthcare and medical research. Orthanc is an open-source, cross-platform software (Linux/Windows/Mac OS X)

The Orthanc Ecosystem for Medical Imaging

peer reviewedThis paper reviews the components of Orthanc, a free and open-source, highly versatile ecosystem for medical imaging. At the core of the Orthanc ecosystem, the Orthanc server is a lightweight vendor neutral archive that provides PACS managers with a powerful environment to automate and optimize the imaging flows that are very specific to each hospital. The Orthanc server can be extended with plugins that provide solutions for teleradiology, digital pathology, or enterprise-ready databases. It is shown how software developers and research engineers can easily develop external software or Web portals dealing with medical images, with minimal knowledge of the DICOM standard, thanks to the advanced programming interface of the Orthanc server. The paper concludes by introducing the Stone of Orthanc, an innovative toolkit for the cross-platform rendering of medical images