Abstract
Magnetic Resonance Imaging has become one of the most important tools for anatomic and functional assessment of the complex brain entities. In neurology are present different indicators related with the brain volume measurements, which have a direct impact on several fields such as diagnosis, surgical planning, study of pathologies, disease preventing and tracking the evolution of diseases under (or not) medical treatments, etc. In this work we propose a new automatic brain volumetry estimation method based on the suitable combination of histogram analysis, optimal thresholding, prior geometric information and mathematical morphology techniques. To validate our method we compare our results with three different well established methods in the neuroscience community: Brain Extraction Tool, Brain Suite and Statistical Parametric Mapping. A dataset of 25 patient studies were evaluated concerning to precision, resolution as well as inter-examination features and statistically we demonstrated that our method present competitive results in relation to the others.

Abstract
Increasingly, medical institutions have access to clinical information through computers. The need to process and manage the large amount of data is motivating the recent interest in semantic approaches. Data regarding vaccination records is a common in such systems. Also, being vaccination is a major area of concern in health policies, numerous information is available in the form of clinical guidelines. However, the information in these guidelines may be difficult to access and apply to a specific patient during consultation. The creation of computer interpretable representations allows the development of clinical decision support systems, improving patient care with the reduction of medical errors, increased safety and satisfaction. This paper describes the method used to model and populate a vaccination ontology and the system which recognizes vaccination information on medical texts. The system identifies relevant entities on medical texts and populates an ontology with new instances of classes. An approach to automatically extract information regarding inter-class relationships using association rule mining is suggested.

Abstract
VITRUVsim is a numerical tool with as much as possible physics included. Inputs are the source parameters (flux, morphology, position...) and outputs are sequences of observed fringes and/or reduced visibilities. VITRUVsim is written in a portable and free language Yorick(4).

Abstract
The breast cancer conservative treatment. cosmetic results (BCCT. core) is a new software tool created for the automatic and objective evaluation of the aesthetic result of BCCT. It makes use of a face-only photographic view of each patient and might thus have been considered insufficient for an accurate evaluation, as others have used multiple views of each patient. The purpose of this work is to compare the performance of the BCCT. core (using face-only views) with a subjective expert analysis using both the face-only and four-view assessment. Photographs in four-views of 150 patients, were evaluated by a panel of experts and a consensus classification was obtained. The agreement between the consensus and the BCCT. core (face-only view) was calculated using the kappa (k) and weighted kappa (wk) statistics. Face-only views, of the same 150 patients, were subsequently sorted out in a different order and sent for individual evaluation by three specialists from the previous panel of experts. The individual agreement between the face-only view and the four-view evaluation by each of the three experts and the consensus was calculated using the same methods. Obtained results were compared to the BCCT. core performance. The software obtained a moderate agreement with the consensus (k = 0.57; wk = 0.68). The highest value of agreement, from the three experts, between the four-view evaluation and the consensus was identical to the software agreement (k = 0.55; wk = 0.67). In the face-only view experiment, the highest value of agreement between the experts and the consensus was only fair (k = 0.37; wk = 0.54). Performance of the software was thus considered equal to that obtained by experts using a four-view evaluation.

Abstract
Cutting and packing problems involving irregular shapes is an important problem variant with a wide variety of industrial applications. Despite its relevance to industry, research publications are relatively low when compared to other cutting and packing problems. One explanation offered is the perceived difficulty and substantial time investment of developing a geometric tool box to assess computer generated solutions. In this paper we set out to provide a tutorial covering the core geometric methodologies currently employed by researchers in cutting and packing of irregular shapes. The paper is not designed to be an exhaustive survey of the literature but instead will draw on the literature to illustrate the theory and implementation of the approaches. We aim to provide a sufficiently instructive description to equip new and current researchers in the area to select the most appropriate methodology for their needs.

Abstract
Airborne Self-Separation is a new concept of dynamic management of air traffic flow, where pilots are allowed to select their flight paths in real-time. In this new operational concept, each aircraft is guided by an automated decision procedure and, based on the available information, enters into negotiations with surrounding aircraft in order to coordinate actions and avoid collisions. In this work, we explore the possibility of combining an approach based on Satisficing Game Theory together with fault-tolerant protocols to obtain a robust approach for conflict resolution and air traffic optimization in the context of Airborne Self-Separation. Copyright 2008 ACM.