Technique de reconstruction itérative VEO : évaluation en tomodensitométrie thoracique chez l'enfant.

Objectifs: Evaluer la technique de reconstruction itérative VEO en tomodensitométrie (TDM) du thorax chez l'enfant. Matériels et méthodes: Etude prospective, basée sur 20 patients (7-18 ans), suivis pour mucoviscidose et adressés pour TDM de suivi. Dix patients (groupe A) ont eu une acquisition basse-dose habituelle (BD). Dix patients (groupe B) ont eu une acquisition très-basse-dose (TBD) et ultra-basse-dose (UBD). Les acquisitions BD étaient reconstruites par rétroprojection filtrée (RPF), les acquisitions TBD et UBD étaient reconstruites par RPF et VEO. L'évaluation de VEO était basée sur la réduction de dose et la qualité des images (mesures de bruit et scores de visualisation des structures pulmonaires). Résultats: Une réduction de dose d'environ 50% était obtenue dans le groupe B. La réduction du bruit en VEO par rapport aux RPF était de 55% en TBD et de 75% en UBD. En VEO, une amélioration des scores de visualisation des structures pulmonaires était obtenue en TBD et UBD. Cependant, en VEO-UBD, la visualisation des structures distales demeuraient parfois insuffisante et celle des structures proximales était altérée par une modification de texture de l'image. Conclusion: Malgré une altération possible de la texture de l'image en UBD, la technique de reconstruction VEO est performante en réduction de dose et amélioration des images.

Augmented state Kalman filtering for AUV navigation

Addresses the problem of estimating the motion of an autonomous underwater vehicle (AUV), while it constructs a visual map ("mosaic" image) of the ocean floor. The vehicle is equipped with a down-looking camera which is used to compute its motion with respect to the seafloor. As the mosaic increases in size, a systematic bias is introduced in the alignment of the images which form the mosaic. Therefore, this accumulative error produces a drift in the estimation of the position of the vehicle. When the arbitrary trajectory of the AUV crosses over itself, it is possible to reduce this propagation of image alignment errors within the mosaic. A Kalman filter with augmented state is proposed to optimally estimate both the visual map and the vehicle position

Simulit, un modèle de simulation pour la planification hospitalière. [Simulit, a simulation model for hospital planning].

The aim of this computerized simulation model is to provide an estimate of the number of beds used by a population, taking into accounts important determining factors. These factors are demographic data of the deserved population, hospitalization rates, hospital case-mix and length of stay; these parameters can be taken either from observed data or from scenarii. As an example, the projected evolution of the number of beds in Canton Vaud for the period 1893-2010 is presented.

Improving Searching and Browsing Capabilities of Learning Object Repositories

Learning object repositories are a basic piece of virtual learning environments used for content management. Nevertheless, learning objects have special characteristics that make traditional solutions for content management ine ective. In particular, browsing and searching for learning objects cannot be based on the typical authoritative meta-data used for describing content, such as author, title or publicationdate, among others. We propose to build a social layer on top of a learning object repository, providing nal users with additional services fordescribing, rating and curating learning objects from a teaching perspective. All these interactions among users, services and resources can be captured and further analyzed, so both browsing and searching can be personalized according to user pro le and the educational context, helping users to nd the most valuable resources for their learning process. In this paper we propose to use reputation schemes and collaborative filtering techniques for improving the user interface of a DSpace based learning object repository.